SlideShare una empresa de Scribd logo
1 de 7
Descargar para leer sin conexión
International Journal of Electrical and Computer Engineering (IJECE)
Vol. 8, No. 5, October 2018, pp. 2788~2794
ISSN: 2088-8708, DOI: 10.11591/ijece.v8i5.pp2788-2794  2788
Journal homepage: http://iaescore.com/journals/index.php/IJECE
Evaluation and Analysis of Rate Control Methods for
H.264/AVC and MPEG-4 Video Codec
Imran Ullah Khan, M. A. Ansari, S. Hasan Saeed, Kakul Khan
Integral University, India
Article Info ABSTRACT
Article history:
Received Feb 19, 2018
Revised Aug 25, 2018
Accepted Sep 10, 2018
Audio, image and video signals produce a vast amount of data. The only
solution of this problem is to compress data before storage and transmission.
In general there is the three crucial terms as, Bit Rate Reduction, Fast Data
Transfer and Reduction in Storage. Rate control is a vigorous factor in video
coding. In video communications, rate control must ensure the coded
bitstream can be transmitted effectively and make full use of the narrow
bandwidth. There are various test models usually suggested by a standard
during the development of video codes models in order to video coding
which should be suffienciently be efficient based on H.264 at very low bit
rate. These models are Test Model Number 5 (TMN5), Test Model Number
8 for H.263, and Verification Model 8 (VM8) for MPEG-4 and H.264 etc. In
this work, Rate control analysis for H.264, MPEG-4 performed. For Rate
control analysis test model verification model version 8.0 is adopted.
Keyword:
Bit rate
Coefficient of correlation
PSNR
Quantization parameter and
rate control
Copyright © 2018 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Imran Ullah Khan,
Integral University, Lucknow, India.
Email: imranuk79@gmail.com
1. INTRODUCTION
Standardization maintains its key place in those technologies backed by a large number of
manufacturers, and thus, a standard form in video coding is a necessary aspect. Discrete Cosine Transform
(DCT) base coding algorithm oscillates the resulting bit rate according to the video sequence nature.
Modification in the size, the texture, and the speed of a moving object are among the main causes of bit rate
change. A rate controller achieves a well-reconstructed video quality and transmission of constant bit rate
over a circuit switched network [1, 2]. The bit rate fluctuations should not be present in reconstructed video,
which is usually achieved by means of a transmission buffer that is inherent in the interframe coding scheme.
The H.261 was developed as first video codec for video conferencing International Telecommunication
Union-Telecommunication sector.
Compression performance of H.263 developed by ITU-T can be improved by stimulating three rate
control methods: In Constant Bit Rate application, there is an important issue of both bit rate control and
buffer regulation. There are two constraints-low-latency and buffer constraints-for which scalable bit rate
control (SRC) has been designed. For achieving the target bit rate, a variable frame rate is usually done.
Almost same technique can also extend to macroblock layers and slice. The two rate control methods for
MPEG-4 that are used in this work are as follows:
a. OFFLINE: In this option, the bit rate control takes the form of changing the quantization levels over the
frames encoded after the first I- or P-frame. There will be no frame skipping in this mode [3, 4].
b. ONLINE: In this mode, the bit rate control is accomplished by adaptively changing the quantization
values at the macroblock level.Frame skipping is allowed in this mode [4].
Int J Elec & Comp Eng ISSN: 2088-8708 
Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan)
2789
2. FUNCTION OF RATE CONTROL
For an available network, bandwidth rate control encodes the video bandwidth, ensures that the
coded bitstream can be transmitted successfully, and utilizes the limited bandwidth. On the other hand, we
can say that the channel of the resulting video output may be fixed or variable transmission rate. If successive
frames are used in video sequence, they are very similar and each frame output bit changes with the operating
input image. Therefore, the bitstream should acquire the characteristics of a rapidly changing of frame [5-7].
3. OVERVIEW OF RATE CONTROL
However, using a buffer has few limitations (such as the propagation delay of a real time
communication will be longer if buffer is too big which is not accepted). Video coding algorithm of
mainstream DCT quantization method is adopted to eliminate video signals, the visual physiology redundant
than lossless higher compression ratio and will not decrease the video quality significantly [8]. Distortion
factor D can be select as any cost function, absolute square cost function etc.In the image coding D is
computed as:
2
y)]g(x,y)f(x,[E{D −=
4. H.264 AND ITS PARAMETERS
There are several additional features to make it superior over its predecessor, are listed
below [9, 10]: There are two context schemes, CAVLC (context-adaptive variable-length coding) and
CABAC (context-adaptive binary arithmetic coding), to increase coding efficiency. In H.264 there are
various sizes & shapes of blocks of many type for motion compensation, such as 8x4, 4*8 and 4*4, are
supported. ¼ pixel motion estimation improves prediction accuracy. The H.264/AVC encoder and decoder is
shown in Figure 1 and 2.
Figure 1. Block diagram of H.264/AVC encoder
Figure 2. Block diagram of H.264/AVC decoder
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794
2790
5. MPEG-4 AND ITS PARAMETERS
A transmission buffer is usually needed to smooth out the bit rate fluctuations, which are inherent in
the interframe coding scheme [11, 12]. Constant bit rate over a switched network [13] for transmission is the
main objective of rate controller. There are many advanced features of MPEG-4 which are not present in
MPEG-1/2. The block diagram of a MPEG-4 video coder is shown in Figure 3.
Figure 3. Block diagram of MPEG-4 coder
Where: DCT=Discrete Cosine Transform
IDCT=Inverse Discrete Cosine Transform
ME/MC=Motion Estimation/Motion Compensation Pred. -Prediction
6. RATE CONTROL SCHEME IN MPEG-4
The MPEG group officially initiated an MPEG-4 adopted VM8 (Verification Model 8) to realize
rate control. MPEG-4 adopted VM8 (Verification Model 8) to realize rate control. There are five steps in the
MPEG-4 VM8 rate control algorithm shown in Figure 4, Initialization Computation of the target bit rate
(TBR) before encoding the computation of TBR is based on the bits available and the last encoded frame bits
[14]. Encoding current frame after encoding, model parameters are updated [15].
Figure 4. Procedure of the MPEG-4 VM8 rate control algorithm
Int J Elec & Comp Eng ISSN: 2088-8708 
Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan)
2791
Where: MAD=Mean Absolute Difference
Q=Quantizer Parameter
T=Target Bit
7. RATE CONTROL SCHEME IN H.264
In this proposed work, the rate control for the forecast frame done after encoding the I-frames using
the base line profile encoding i.e. CAVLC encoding and taking the mention data from it. The rate control
block diagram Figure 3 explains how the QP parameter is approximated. The residuals between the current
and reference frame is estimated. Mean Absolute Deviation (MAD) values are obtained by summing the
residuals. The value of QP is initialized to a range manually [16]. Figure 5 shows rate control by estimating
the quantization parameters or rate control algorithm. QP limiter is used to limit the demanded QP to a range
and the parameters are estimated for the procedure By using these parameters, rate control is performed on
the input video to get an output video. This procedure ensures controlled bit-rate and better compression
ratio.
Figure 5. Rate control by estimating the quantization parameters
8. SIMULATION, IMPLEMENTATION DETAILS AND RESULTS OBTAINED
Performance metrics are used to assess the quality of the obtained video. The test video sequence is
Heart at frame rate 24 per second. The performance metrics on which the video quality adjudged are
Compression ratio, Mean Square Error, Peak Signal to Noise Ratio, correlation coefficient, PRD and SSIM.
∑∑∑∑
∑∑
−
=
−
=
−
=
−
=
−
=
−
=
=
1X
0x
1Y
0y
2
1X
0x
1Y
0y
2
1X
0x
1Y
0y
y)e(x,y)i(x,
y)e(x,y)i(x,
COC
(1)
Mean square error (MSE)
∑∑= =
−=
X
1x
Y
1y
2
y)]e(x,y)[i(x,
XY
1
MSE (2)
Where; i (x, y)=Intensity of input pixel (for each U, V,Y)
e (x, y)=Intensity of output pixel (for each U, V,Y)
The PSNR for each frame is defined as:
Encoder Rate Quantization
Model
Quantization
Parameter
Limiter
Estimated
Quantization
Parameter
Quantization
Parameter
Initializer
Group of Picture
(GOP) Bit
Allocation
Complexity
Estimation
Demanded Bit
rate Estimation
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794
2792
V)U,Y,each(for)
MSE
255
(20log)
MSE
255
(log10PSNR 10
2
10 == (3)
The PSNR for entire video sequence is defined in terms of Average PSNR
V)&Ueach(Y,forPSNR(i)
t
i
PSNRAverage
t
1i
∑=
= (4)
Where t is total number of frames in video and PSNR (i) is the PSNR value for ith
frame. It should be noted
here that improvement in the subjective quality of decoded video is acquire at the cost of increased
computational is complicated. The SSIM is a structural similarity index (similarity measuring full reference
metric between two images, means the measurement of image quality support on a mention initial
uncompressed or distortion-free image). It can also be understood as an improved version of traditional
methods like PSNR and MSE, generally which is inconsistent with human eye perception.
)cσ)(σcμ(μ
)c)(2σcμ(2μ
y)SSIM(x,
2
2
y
2
x1
2
y
2
x
2xy1yx
++++
++
= (5)
Where
c1=(k1L)2
and c2=(k2L)2
In the equation of c1, c2 and L is the dynamic range of the pixel-values and k1=0.01, k2=0.03 by
default. Equation 5 of SSIM is appropriate only on Y ie. luma. Its value ranges from -1 and 1, where 1 is only
possible if two sets of data are identical. Generally it is considered on window sizes of 8×8. Figure 6 shows
comparative performance with reference to SSIM. Figure 7 and shows sequence Heart and Mobile
respectively.
Table 1 is elaborating the SSIM profile for sequence Shields. Table 2 tells about the detail of
sequence Mobile. Table 3 gives the summary of results obtained in this work regarding the performance of
MPEG-4 codec for various rate control methods at 14.4 and 100 kbps target bit rates. It is observed that
online and offline rate control methods have almost same performance as far PSNR is concerned. When rate
control is applied and target bit rate is reduced, it is observed that the PSNR, bit rate and storage requirement
also reduces. No control method corresponds to fixed quantization parameter. Table 4 gives comparative
statement for quantization parameter, mean square error, peak signal to noise ratio, compression ratio and
similarity index. Detail of sequence mobile is illustrated in Table 2.
Figure 6. Comparative Performance of MPEG-4 Video Coder for Shields video sequence for Base profile
and CABAC enabled, SSIM profile
Int J Elec & Comp Eng ISSN: 2088-8708 
Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan)
2793
Sequence title: Heart
Resolution: 176x144
Figure 7. Snapshot of “Heart” video
sequence, frame 30
Figure 7. Snapshot of “Mobile” video sequence
Table 1. Heart Video Sequence Simulation Results For Base Profile and Cabac Enabled
Data Rate (Mbps) PSNR(dB) PSNR(dB) SSIM SSIM
Base Profile CABAC Enabled Base Profile CABAC Enabled
0 31.9 32.3 0.88 0.88
0.2 37.3 37.6 0.93 0.932
0.5 42 42.4 0.96 0.963
0.8 44.5 45 0.972 0.972
1 45.9 46.5 0.974 0.974
1.2 46.9 47.4 0.974 0.9755
1.5 47.9 48.5 0.976 0.9764
1.8 48.8 49.7 0.977 0.978
2 49.7 50.2 0.979 0.9798
2.2 50.5 50.9 0.98 0.982
2.5 51.1 51.6 0.981 0.984
Table 2. Detail of the Video Sequence Mobile
S.No. Detail of Sequence
1 Name Mobile
2 Size CIF (352x288)
3 Total size[byte] 23612683
4 Frames 300
5 Playing time[s] 10.03Min
6 frame size[byte] 79
7 Max frame size[byte] 118449
8 Mean frame size[byte] 78447.45
Table 3. Mobile Video Sequence Simulation Results for Mpeg-4 Video Codec
Target bit
rate
(Kbps)
Various Parameter
(a)No Control
over bit rate
(b) Bit Rate
Control
Offline
(c) Bit rate Control
Online(with frame
skipping)
(d) Bit rate Control
Online(without frame
skipping
Average PSNR Y 48.44 34.12 34.55 34.54
100
Average PSNR U 49.78 38.15 38.83 39.12
Average PSNR V 49.88 38.35 38.87 39.41
Bit rate (kb/sec) 98.95 99.5 99.9 99.9
Compression ratio 7:01 95:01:00 95:01:00 95:01:00
Average PSNR Y 44.44 27.85 27.83 27.49
14.4
Average PSNR U 45.78 33.7 34.75 33.68
Average PSNR V 46.36 34.15 35.17 33.95
Bit rate (kb/sec) 1478.3 44 15.7 27
Compression Ratio 7:01 205:01:00 556:01:00 304:01:00
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794
2794
Table 4. Comparative Statement for Qp, Mse, Psnr, Cr And Ssim
S.No. Quantization Parameter MSE PSNR SSIM Compression Ratio
1. 10 0.32 54.33 0.99 11.5
2. 15 0.51 52.12 0.98 13.3
3. 20 1.82 47.24 0.96 25.4
4. 25 2.99 43.44 0.95 29.3
5. 27 3.42 42.89 0.94 34.6
6. 30 7.991 39.21 0.91 39.7
7. 35 14.78 35.11 0.85 42.4
8. 40 20.71 33.2 0.78 44.0
9. 45 28.62 31.6 0.73 44.9
10. 50 39.12 30.7 0.69 46.1
9. CONCLUSION
In this paper H.264 and MPEG-4 basic features are discussed along with how the performance is
influenced by rate controller for H.264/AVC and MPEG-4. There are test model VM8 verification model
version 8.0 is used for the analysis of H.264/AVC and MPEG-4. In constant bit-rate applications, both on-
line and off-line rate control methods gives the obtained bit-rate very close to the target bit rate (TBR) for a
moderate target bit rates (medium and high). However, for low bit rate applications only online method
results in the actual bit-rate being close to the TBR bit rate. There are many other parameters and
functionalities in MPEG-4 which are aimed to be investigated in future.
REFERENCES
[1] Manjanaik.N, Manjunath.R “Intra Frame Coding for Advanced Video Coding Standard to Control PSNR and
Bitrate Using Gaussian Pulse” International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–
6378, Volume-2, Issue-5, March 2014.
[2] T. Bernatin, G. Sundari, B. Gayethri, Swarna Ramesh, “ Performance analysis of Rate Control Scheme in H.264
Video Coding” Indian Journal of Science & Technology, Vol 9(30), Doi:10.17485/ijst/2016/v9i30/99061, August
2016
[3] D.Marpe, T.Wiegand and G.J.Sullivan, “The H.264/MPEG Advance video coding standard and its applications”,
IEEE Communications Magazine, vol.44, no.8, pp.134-144, Aug.2006.
[4] I. U. Khan, M.A. Ansari “Evaluation of Deblocking Filter for H.263 Video Codec & Proposed Algorithm for
Entropy Coding for MPEG-4 Video Codec” has been published in “International Journal of Control Theory and
Applications” (No.2 2015).
[5] J. Ribas-Conklin, S. Lei. “Rate control in DCT video coding for low-delay communication.IEEE Trans. Circuit
Syst. Video Technol. Feb 1999, 9(1):172-185
[6] P.Topiwala, G.sullivan, A.Joch, and F.Kossentini, “Performance evaluation of H.26L, TML8 vs. H.263++ and
MPEG-4,”ITU-T Q.6/SG6 (VCEG) Tech. Rep. N8, sept.2001.
[7] Hung-Ju Lee, Ya-Qin Zhang. Scalable Rate Control for MPEG-4 Video. IEEE Trans. Circuits 64 and Systems for
Video Technology2000, 10(6): 878-894.
[8] I. U. Khan, M.A. Ansari “Data Partitioning and MDC for the SPECK Coder for real time applications over wireless
channel” has been published in “Indian Journal of Industrial and Applied Mathematics”, Volume 6 , Issue 1,Jan-
June (2015) pp. 57 - 72.
[9] Liao K-Y, Yang J-F, Sun M-T. Rate-Distortion cost estimation for H.264/AVC. IEEE Transactions on Circuits and
System Video Coding Technology. 2010 Jan; 20(1):38–49.
[10] Bernatin T, Sundari G. Video compression based on Hybrid transform and quantization with Huffman coding for
video code. International Conference on Control, Instrumentation, Communication and Computational
Technologies (ICCICCT). 2014 Jul; 4(7):476–80.
[11] I. U. Khan, M.A. Ansari,” Overview and Implementation of Intrapredictions for H.264/AVC Video Codec,
International Journal of Electronics and Communication Engineering (IJECE) Vol. 3, Issue 4, July 2014, 177-186.
[12] M.Ghanbari, “Video Coding: an introduction to standard codes;”IEE press, London 1999. “Video coding for low
bit rate communication ITU-T, Recommendation H.263, ver.1, 1995.
[13] Xiang Li, Nobert Oertel, Laplace distribution based Lagrangian rate distrortion optimization for hybrid video
coding. IEEE Transction on Circuits and Systems. 2009; 19(2): 193-205
[14] James C, Alex Mm, An efficient video codecbased on H.264/AVC standard.IRACST. International Journal of
Computer Networks and wireless communications, 2014 Apr;4(2):1-4.
[15] Ramu JG, Sathya S Permence evaluation of basic compression methods for different stalellite imaginary, Indan
Journal Sci. & Tech. .2015 Aug;8(19): 1-8.
[16] Various video sequences http:www.ubvideo.com Date accessed: 01/07/2015.

Más contenido relacionado

La actualidad más candente

A study of throughput for iu cs and iu-ps interface in umts core network
A study of throughput for iu cs and iu-ps interface in umts core networkA study of throughput for iu cs and iu-ps interface in umts core network
A study of throughput for iu cs and iu-ps interface in umts core network
Pfedya
 
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
Cemal Ardil
 
Video coding technology proposal by
Video coding technology proposal by Video coding technology proposal by
Video coding technology proposal by
Videoguy
 
LTE Reviews - PCI Analysis
LTE Reviews - PCI AnalysisLTE Reviews - PCI Analysis
LTE Reviews - PCI Analysis
paulo_campolina
 

La actualidad más candente (18)

AN EFFICIENT VITERBI DECODER
AN EFFICIENT VITERBI DECODERAN EFFICIENT VITERBI DECODER
AN EFFICIENT VITERBI DECODER
 
Current developments in video quality: From the emerging HEVC standard to tem...
Current developments in video quality: From the emerging HEVC standard to tem...Current developments in video quality: From the emerging HEVC standard to tem...
Current developments in video quality: From the emerging HEVC standard to tem...
 
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
 
Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2...
Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2...Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2...
Where to Encode: A Performance Analysis of Intel x86 and Arm-based Amazon EC2...
 
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
 
High Performance MAC Unit for FFT Implementation
High Performance MAC Unit for FFT Implementation High Performance MAC Unit for FFT Implementation
High Performance MAC Unit for FFT Implementation
 
FPGA Implementation of Efficient Viterbi Decoder for Multi-Carrier Systems
FPGA Implementation of Efficient Viterbi Decoder for  Multi-Carrier SystemsFPGA Implementation of Efficient Viterbi Decoder for  Multi-Carrier Systems
FPGA Implementation of Efficient Viterbi Decoder for Multi-Carrier Systems
 
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
 
A study of throughput for iu cs and iu-ps interface in umts core network
A study of throughput for iu cs and iu-ps interface in umts core networkA study of throughput for iu cs and iu-ps interface in umts core network
A study of throughput for iu cs and iu-ps interface in umts core network
 
WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile D...
WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile D...WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile D...
WISH: User-centric Bitrate Adaptation for HTTP Adaptive Streaming on Mobile D...
 
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
Bip based-alarm-declaration-and-clearing-in-sonet-networks-employing-automati...
 
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
IMPLEMENTATION OF A NEW IR-UWB SYSTEM BASED ON M-OAM MODULATION ON FPGA COMPO...
 
IRJET- A New High Speed Wide Fan in Carry Look Ahead Adder Design using M...
IRJET-  	  A New High Speed Wide Fan in Carry Look Ahead Adder Design using M...IRJET-  	  A New High Speed Wide Fan in Carry Look Ahead Adder Design using M...
IRJET- A New High Speed Wide Fan in Carry Look Ahead Adder Design using M...
 
Video coding technology proposal by
Video coding technology proposal by Video coding technology proposal by
Video coding technology proposal by
 
LTE Reviews - PCI Analysis
LTE Reviews - PCI AnalysisLTE Reviews - PCI Analysis
LTE Reviews - PCI Analysis
 
EPIQ'21: Days of Future Past: An Optimization-based Adaptive Bitrate Algorith...
EPIQ'21: Days of Future Past: An Optimization-based Adaptive Bitrate Algorith...EPIQ'21: Days of Future Past: An Optimization-based Adaptive Bitrate Algorith...
EPIQ'21: Days of Future Past: An Optimization-based Adaptive Bitrate Algorith...
 
Designing of Adders and Vedic Multiplier using Gate Diffusion Input
Designing of Adders and Vedic Multiplier using Gate Diffusion InputDesigning of Adders and Vedic Multiplier using Gate Diffusion Input
Designing of Adders and Vedic Multiplier using Gate Diffusion Input
 
Policy-driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-driven Dynamic HTTP Adaptive Streaming Player EnvironmentPolicy-driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-driven Dynamic HTTP Adaptive Streaming Player Environment
 

Similar a Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec

Paper id 2120148
Paper id 2120148Paper id 2120148
Paper id 2120148
IJRAT
 
10.1.1.184.6612
10.1.1.184.661210.1.1.184.6612
10.1.1.184.6612
NITC
 
H04011 04 5361
H04011 04 5361H04011 04 5361
H04011 04 5361
IJMER
 
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
ijiert bestjournal
 
Machine learning-based energy consumption modeling and comparing of H.264 and...
Machine learning-based energy consumption modeling and comparing of H.264 and...Machine learning-based energy consumption modeling and comparing of H.264 and...
Machine learning-based energy consumption modeling and comparing of H.264 and...
IJECEIAES
 

Similar a Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec (20)

Paper id 2120148
Paper id 2120148Paper id 2120148
Paper id 2120148
 
10.1.1.184.6612
10.1.1.184.661210.1.1.184.6612
10.1.1.184.6612
 
H04011 04 5361
H04011 04 5361H04011 04 5361
H04011 04 5361
 
HARDWARE SOFTWARE CO-SIMULATION OF MOTION ESTIMATION IN H.264 ENCODER
HARDWARE SOFTWARE CO-SIMULATION OF MOTION ESTIMATION IN H.264 ENCODERHARDWARE SOFTWARE CO-SIMULATION OF MOTION ESTIMATION IN H.264 ENCODER
HARDWARE SOFTWARE CO-SIMULATION OF MOTION ESTIMATION IN H.264 ENCODER
 
Design and Implementation of HDMI Transmitter
Design and Implementation of HDMI TransmitterDesign and Implementation of HDMI Transmitter
Design and Implementation of HDMI Transmitter
 
A REAL-TIME H.264/AVC ENCODER&DECODER WITH VERTICAL MODE FOR INTRA FRAME AND ...
A REAL-TIME H.264/AVC ENCODER&DECODER WITH VERTICAL MODE FOR INTRA FRAME AND ...A REAL-TIME H.264/AVC ENCODER&DECODER WITH VERTICAL MODE FOR INTRA FRAME AND ...
A REAL-TIME H.264/AVC ENCODER&DECODER WITH VERTICAL MODE FOR INTRA FRAME AND ...
 
Rate Distortion Performance for Joint Source Channel Coding of JPEG image Ove...
Rate Distortion Performance for Joint Source Channel Coding of JPEG image Ove...Rate Distortion Performance for Joint Source Channel Coding of JPEG image Ove...
Rate Distortion Performance for Joint Source Channel Coding of JPEG image Ove...
 
H264 final
H264 finalH264 final
H264 final
 
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
DIGITAL IMAGE WATERMARKING OF COMPRESSED IMAGE USING JPEG 2000 AND ENCRYPTION...
 
High Efficiency Video Codec
High Efficiency Video CodecHigh Efficiency Video Codec
High Efficiency Video Codec
 
IRJET- A Hybrid Image and Video Compression of DCT and DWT Techniques for H.2...
IRJET- A Hybrid Image and Video Compression of DCT and DWT Techniques for H.2...IRJET- A Hybrid Image and Video Compression of DCT and DWT Techniques for H.2...
IRJET- A Hybrid Image and Video Compression of DCT and DWT Techniques for H.2...
 
Machine learning-based energy consumption modeling and comparing of H.264 and...
Machine learning-based energy consumption modeling and comparing of H.264 and...Machine learning-based energy consumption modeling and comparing of H.264 and...
Machine learning-based energy consumption modeling and comparing of H.264 and...
 
An Overview on Multimedia Transcoding Techniques on Streaming Digital Contents
An Overview on Multimedia Transcoding Techniques on Streaming Digital ContentsAn Overview on Multimedia Transcoding Techniques on Streaming Digital Contents
An Overview on Multimedia Transcoding Techniques on Streaming Digital Contents
 
Design of an Efficient Reconfigurable Fir Filter for Multi Standard Digital u...
Design of an Efficient Reconfigurable Fir Filter for Multi Standard Digital u...Design of an Efficient Reconfigurable Fir Filter for Multi Standard Digital u...
Design of an Efficient Reconfigurable Fir Filter for Multi Standard Digital u...
 
Efficient video compression using EZWT
Efficient video compression using EZWTEfficient video compression using EZWT
Efficient video compression using EZWT
 
C0161018
C0161018C0161018
C0161018
 
C0161018
C0161018C0161018
C0161018
 
Performance Enhancement for Quality Inter-Layer Scalable Video Coding
Performance Enhancement for Quality Inter-Layer Scalable Video CodingPerformance Enhancement for Quality Inter-Layer Scalable Video Coding
Performance Enhancement for Quality Inter-Layer Scalable Video Coding
 
40120140504006
4012014050400640120140504006
40120140504006
 
C010421720
C010421720C010421720
C010421720
 

Más de IJECEIAES

Predicting churn with filter-based techniques and deep learning
Predicting churn with filter-based techniques and deep learningPredicting churn with filter-based techniques and deep learning
Predicting churn with filter-based techniques and deep learning
IJECEIAES
 
Automatic customer review summarization using deep learningbased hybrid senti...
Automatic customer review summarization using deep learningbased hybrid senti...Automatic customer review summarization using deep learningbased hybrid senti...
Automatic customer review summarization using deep learningbased hybrid senti...
IJECEIAES
 
Situational judgment test measures administrator computational thinking with ...
Situational judgment test measures administrator computational thinking with ...Situational judgment test measures administrator computational thinking with ...
Situational judgment test measures administrator computational thinking with ...
IJECEIAES
 
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
IJECEIAES
 
Application of deep learning methods for automated analysis of retinal struct...
Application of deep learning methods for automated analysis of retinal struct...Application of deep learning methods for automated analysis of retinal struct...
Application of deep learning methods for automated analysis of retinal struct...
IJECEIAES
 
Predictive modeling for breast cancer based on machine learning algorithms an...
Predictive modeling for breast cancer based on machine learning algorithms an...Predictive modeling for breast cancer based on machine learning algorithms an...
Predictive modeling for breast cancer based on machine learning algorithms an...
IJECEIAES
 

Más de IJECEIAES (20)

Predicting churn with filter-based techniques and deep learning
Predicting churn with filter-based techniques and deep learningPredicting churn with filter-based techniques and deep learning
Predicting churn with filter-based techniques and deep learning
 
Taxi-out time prediction at Mohammed V Casablanca Airport
Taxi-out time prediction at Mohammed V Casablanca AirportTaxi-out time prediction at Mohammed V Casablanca Airport
Taxi-out time prediction at Mohammed V Casablanca Airport
 
Automatic customer review summarization using deep learningbased hybrid senti...
Automatic customer review summarization using deep learningbased hybrid senti...Automatic customer review summarization using deep learningbased hybrid senti...
Automatic customer review summarization using deep learningbased hybrid senti...
 
Ataxic person prediction using feature optimized based on machine learning model
Ataxic person prediction using feature optimized based on machine learning modelAtaxic person prediction using feature optimized based on machine learning model
Ataxic person prediction using feature optimized based on machine learning model
 
Situational judgment test measures administrator computational thinking with ...
Situational judgment test measures administrator computational thinking with ...Situational judgment test measures administrator computational thinking with ...
Situational judgment test measures administrator computational thinking with ...
 
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile...
 
An overlapping conscious relief-based feature subset selection method
An overlapping conscious relief-based feature subset selection methodAn overlapping conscious relief-based feature subset selection method
An overlapping conscious relief-based feature subset selection method
 
Recognition of music symbol notation using convolutional neural network
Recognition of music symbol notation using convolutional neural networkRecognition of music symbol notation using convolutional neural network
Recognition of music symbol notation using convolutional neural network
 
A simplified classification computational model of opinion mining using deep ...
A simplified classification computational model of opinion mining using deep ...A simplified classification computational model of opinion mining using deep ...
A simplified classification computational model of opinion mining using deep ...
 
An efficient convolutional neural network-extreme gradient boosting hybrid de...
An efficient convolutional neural network-extreme gradient boosting hybrid de...An efficient convolutional neural network-extreme gradient boosting hybrid de...
An efficient convolutional neural network-extreme gradient boosting hybrid de...
 
Generating images using generative adversarial networks based on text descrip...
Generating images using generative adversarial networks based on text descrip...Generating images using generative adversarial networks based on text descrip...
Generating images using generative adversarial networks based on text descrip...
 
Collusion-resistant multiparty data sharing in social networks
Collusion-resistant multiparty data sharing in social networksCollusion-resistant multiparty data sharing in social networks
Collusion-resistant multiparty data sharing in social networks
 
Application of deep learning methods for automated analysis of retinal struct...
Application of deep learning methods for automated analysis of retinal struct...Application of deep learning methods for automated analysis of retinal struct...
Application of deep learning methods for automated analysis of retinal struct...
 
Proposal of a similarity measure for unified modeling language class diagram ...
Proposal of a similarity measure for unified modeling language class diagram ...Proposal of a similarity measure for unified modeling language class diagram ...
Proposal of a similarity measure for unified modeling language class diagram ...
 
Efficient criticality oriented service brokering policy in cloud datacenters
Efficient criticality oriented service brokering policy in cloud datacentersEfficient criticality oriented service brokering policy in cloud datacenters
Efficient criticality oriented service brokering policy in cloud datacenters
 
System call frequency analysis-based generative adversarial network model for...
System call frequency analysis-based generative adversarial network model for...System call frequency analysis-based generative adversarial network model for...
System call frequency analysis-based generative adversarial network model for...
 
Comparison of Iris dataset classification with Gaussian naïve Bayes and decis...
Comparison of Iris dataset classification with Gaussian naïve Bayes and decis...Comparison of Iris dataset classification with Gaussian naïve Bayes and decis...
Comparison of Iris dataset classification with Gaussian naïve Bayes and decis...
 
Efficient intelligent crawler for hamming distance based on prioritization of...
Efficient intelligent crawler for hamming distance based on prioritization of...Efficient intelligent crawler for hamming distance based on prioritization of...
Efficient intelligent crawler for hamming distance based on prioritization of...
 
Predictive modeling for breast cancer based on machine learning algorithms an...
Predictive modeling for breast cancer based on machine learning algorithms an...Predictive modeling for breast cancer based on machine learning algorithms an...
Predictive modeling for breast cancer based on machine learning algorithms an...
 
An algorithm for decomposing variations of 3D model
An algorithm for decomposing variations of 3D modelAn algorithm for decomposing variations of 3D model
An algorithm for decomposing variations of 3D model
 

Último

AKTU Computer Networks notes --- Unit 3.pdf
AKTU Computer Networks notes ---  Unit 3.pdfAKTU Computer Networks notes ---  Unit 3.pdf
AKTU Computer Networks notes --- Unit 3.pdf
ankushspencer015
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.ppt
MsecMca
 
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
dollysharma2066
 
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort ServiceCall Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Christo Ananth
 
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Christo Ananth
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
dharasingh5698
 

Último (20)

Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - V
 
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
 
AKTU Computer Networks notes --- Unit 3.pdf
AKTU Computer Networks notes ---  Unit 3.pdfAKTU Computer Networks notes ---  Unit 3.pdf
AKTU Computer Networks notes --- Unit 3.pdf
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.ppt
 
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptxBSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
BSides Seattle 2024 - Stopping Ethan Hunt From Taking Your Data.pptx
 
Thermal Engineering Unit - I & II . ppt
Thermal Engineering  Unit - I & II . pptThermal Engineering  Unit - I & II . ppt
Thermal Engineering Unit - I & II . ppt
 
Roadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and RoutesRoadmap to Membership of RICS - Pathways and Routes
Roadmap to Membership of RICS - Pathways and Routes
 
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
 
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
The Most Attractive Pune Call Girls Manchar 8250192130 Will You Miss This Cha...
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort ServiceCall Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
 
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELLPVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
PVC VS. FIBERGLASS (FRP) GRAVITY SEWER - UNI BELL
 
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...
 
KubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghlyKubeKraft presentation @CloudNativeHooghly
KubeKraft presentation @CloudNativeHooghly
 
Call Girls Walvekar Nagar Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Walvekar Nagar Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Walvekar Nagar Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Walvekar Nagar Call Me 7737669865 Budget Friendly No Advance Booking
 
Generative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPTGenerative AI or GenAI technology based PPT
Generative AI or GenAI technology based PPT
 
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...
 
Java Programming :Event Handling(Types of Events)
Java Programming :Event Handling(Types of Events)Java Programming :Event Handling(Types of Events)
Java Programming :Event Handling(Types of Events)
 
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordCCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
 

Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec

  • 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 8, No. 5, October 2018, pp. 2788~2794 ISSN: 2088-8708, DOI: 10.11591/ijece.v8i5.pp2788-2794  2788 Journal homepage: http://iaescore.com/journals/index.php/IJECE Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec Imran Ullah Khan, M. A. Ansari, S. Hasan Saeed, Kakul Khan Integral University, India Article Info ABSTRACT Article history: Received Feb 19, 2018 Revised Aug 25, 2018 Accepted Sep 10, 2018 Audio, image and video signals produce a vast amount of data. The only solution of this problem is to compress data before storage and transmission. In general there is the three crucial terms as, Bit Rate Reduction, Fast Data Transfer and Reduction in Storage. Rate control is a vigorous factor in video coding. In video communications, rate control must ensure the coded bitstream can be transmitted effectively and make full use of the narrow bandwidth. There are various test models usually suggested by a standard during the development of video codes models in order to video coding which should be suffienciently be efficient based on H.264 at very low bit rate. These models are Test Model Number 5 (TMN5), Test Model Number 8 for H.263, and Verification Model 8 (VM8) for MPEG-4 and H.264 etc. In this work, Rate control analysis for H.264, MPEG-4 performed. For Rate control analysis test model verification model version 8.0 is adopted. Keyword: Bit rate Coefficient of correlation PSNR Quantization parameter and rate control Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Imran Ullah Khan, Integral University, Lucknow, India. Email: imranuk79@gmail.com 1. INTRODUCTION Standardization maintains its key place in those technologies backed by a large number of manufacturers, and thus, a standard form in video coding is a necessary aspect. Discrete Cosine Transform (DCT) base coding algorithm oscillates the resulting bit rate according to the video sequence nature. Modification in the size, the texture, and the speed of a moving object are among the main causes of bit rate change. A rate controller achieves a well-reconstructed video quality and transmission of constant bit rate over a circuit switched network [1, 2]. The bit rate fluctuations should not be present in reconstructed video, which is usually achieved by means of a transmission buffer that is inherent in the interframe coding scheme. The H.261 was developed as first video codec for video conferencing International Telecommunication Union-Telecommunication sector. Compression performance of H.263 developed by ITU-T can be improved by stimulating three rate control methods: In Constant Bit Rate application, there is an important issue of both bit rate control and buffer regulation. There are two constraints-low-latency and buffer constraints-for which scalable bit rate control (SRC) has been designed. For achieving the target bit rate, a variable frame rate is usually done. Almost same technique can also extend to macroblock layers and slice. The two rate control methods for MPEG-4 that are used in this work are as follows: a. OFFLINE: In this option, the bit rate control takes the form of changing the quantization levels over the frames encoded after the first I- or P-frame. There will be no frame skipping in this mode [3, 4]. b. ONLINE: In this mode, the bit rate control is accomplished by adaptively changing the quantization values at the macroblock level.Frame skipping is allowed in this mode [4].
  • 2. Int J Elec & Comp Eng ISSN: 2088-8708  Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan) 2789 2. FUNCTION OF RATE CONTROL For an available network, bandwidth rate control encodes the video bandwidth, ensures that the coded bitstream can be transmitted successfully, and utilizes the limited bandwidth. On the other hand, we can say that the channel of the resulting video output may be fixed or variable transmission rate. If successive frames are used in video sequence, they are very similar and each frame output bit changes with the operating input image. Therefore, the bitstream should acquire the characteristics of a rapidly changing of frame [5-7]. 3. OVERVIEW OF RATE CONTROL However, using a buffer has few limitations (such as the propagation delay of a real time communication will be longer if buffer is too big which is not accepted). Video coding algorithm of mainstream DCT quantization method is adopted to eliminate video signals, the visual physiology redundant than lossless higher compression ratio and will not decrease the video quality significantly [8]. Distortion factor D can be select as any cost function, absolute square cost function etc.In the image coding D is computed as: 2 y)]g(x,y)f(x,[E{D −= 4. H.264 AND ITS PARAMETERS There are several additional features to make it superior over its predecessor, are listed below [9, 10]: There are two context schemes, CAVLC (context-adaptive variable-length coding) and CABAC (context-adaptive binary arithmetic coding), to increase coding efficiency. In H.264 there are various sizes & shapes of blocks of many type for motion compensation, such as 8x4, 4*8 and 4*4, are supported. ¼ pixel motion estimation improves prediction accuracy. The H.264/AVC encoder and decoder is shown in Figure 1 and 2. Figure 1. Block diagram of H.264/AVC encoder Figure 2. Block diagram of H.264/AVC decoder
  • 3.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794 2790 5. MPEG-4 AND ITS PARAMETERS A transmission buffer is usually needed to smooth out the bit rate fluctuations, which are inherent in the interframe coding scheme [11, 12]. Constant bit rate over a switched network [13] for transmission is the main objective of rate controller. There are many advanced features of MPEG-4 which are not present in MPEG-1/2. The block diagram of a MPEG-4 video coder is shown in Figure 3. Figure 3. Block diagram of MPEG-4 coder Where: DCT=Discrete Cosine Transform IDCT=Inverse Discrete Cosine Transform ME/MC=Motion Estimation/Motion Compensation Pred. -Prediction 6. RATE CONTROL SCHEME IN MPEG-4 The MPEG group officially initiated an MPEG-4 adopted VM8 (Verification Model 8) to realize rate control. MPEG-4 adopted VM8 (Verification Model 8) to realize rate control. There are five steps in the MPEG-4 VM8 rate control algorithm shown in Figure 4, Initialization Computation of the target bit rate (TBR) before encoding the computation of TBR is based on the bits available and the last encoded frame bits [14]. Encoding current frame after encoding, model parameters are updated [15]. Figure 4. Procedure of the MPEG-4 VM8 rate control algorithm
  • 4. Int J Elec & Comp Eng ISSN: 2088-8708  Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan) 2791 Where: MAD=Mean Absolute Difference Q=Quantizer Parameter T=Target Bit 7. RATE CONTROL SCHEME IN H.264 In this proposed work, the rate control for the forecast frame done after encoding the I-frames using the base line profile encoding i.e. CAVLC encoding and taking the mention data from it. The rate control block diagram Figure 3 explains how the QP parameter is approximated. The residuals between the current and reference frame is estimated. Mean Absolute Deviation (MAD) values are obtained by summing the residuals. The value of QP is initialized to a range manually [16]. Figure 5 shows rate control by estimating the quantization parameters or rate control algorithm. QP limiter is used to limit the demanded QP to a range and the parameters are estimated for the procedure By using these parameters, rate control is performed on the input video to get an output video. This procedure ensures controlled bit-rate and better compression ratio. Figure 5. Rate control by estimating the quantization parameters 8. SIMULATION, IMPLEMENTATION DETAILS AND RESULTS OBTAINED Performance metrics are used to assess the quality of the obtained video. The test video sequence is Heart at frame rate 24 per second. The performance metrics on which the video quality adjudged are Compression ratio, Mean Square Error, Peak Signal to Noise Ratio, correlation coefficient, PRD and SSIM. ∑∑∑∑ ∑∑ − = − = − = − = − = − = = 1X 0x 1Y 0y 2 1X 0x 1Y 0y 2 1X 0x 1Y 0y y)e(x,y)i(x, y)e(x,y)i(x, COC (1) Mean square error (MSE) ∑∑= = −= X 1x Y 1y 2 y)]e(x,y)[i(x, XY 1 MSE (2) Where; i (x, y)=Intensity of input pixel (for each U, V,Y) e (x, y)=Intensity of output pixel (for each U, V,Y) The PSNR for each frame is defined as: Encoder Rate Quantization Model Quantization Parameter Limiter Estimated Quantization Parameter Quantization Parameter Initializer Group of Picture (GOP) Bit Allocation Complexity Estimation Demanded Bit rate Estimation
  • 5.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794 2792 V)U,Y,each(for) MSE 255 (20log) MSE 255 (log10PSNR 10 2 10 == (3) The PSNR for entire video sequence is defined in terms of Average PSNR V)&Ueach(Y,forPSNR(i) t i PSNRAverage t 1i ∑= = (4) Where t is total number of frames in video and PSNR (i) is the PSNR value for ith frame. It should be noted here that improvement in the subjective quality of decoded video is acquire at the cost of increased computational is complicated. The SSIM is a structural similarity index (similarity measuring full reference metric between two images, means the measurement of image quality support on a mention initial uncompressed or distortion-free image). It can also be understood as an improved version of traditional methods like PSNR and MSE, generally which is inconsistent with human eye perception. )cσ)(σcμ(μ )c)(2σcμ(2μ y)SSIM(x, 2 2 y 2 x1 2 y 2 x 2xy1yx ++++ ++ = (5) Where c1=(k1L)2 and c2=(k2L)2 In the equation of c1, c2 and L is the dynamic range of the pixel-values and k1=0.01, k2=0.03 by default. Equation 5 of SSIM is appropriate only on Y ie. luma. Its value ranges from -1 and 1, where 1 is only possible if two sets of data are identical. Generally it is considered on window sizes of 8×8. Figure 6 shows comparative performance with reference to SSIM. Figure 7 and shows sequence Heart and Mobile respectively. Table 1 is elaborating the SSIM profile for sequence Shields. Table 2 tells about the detail of sequence Mobile. Table 3 gives the summary of results obtained in this work regarding the performance of MPEG-4 codec for various rate control methods at 14.4 and 100 kbps target bit rates. It is observed that online and offline rate control methods have almost same performance as far PSNR is concerned. When rate control is applied and target bit rate is reduced, it is observed that the PSNR, bit rate and storage requirement also reduces. No control method corresponds to fixed quantization parameter. Table 4 gives comparative statement for quantization parameter, mean square error, peak signal to noise ratio, compression ratio and similarity index. Detail of sequence mobile is illustrated in Table 2. Figure 6. Comparative Performance of MPEG-4 Video Coder for Shields video sequence for Base profile and CABAC enabled, SSIM profile
  • 6. Int J Elec & Comp Eng ISSN: 2088-8708  Evaluation and Analysis of Rate Control Methods for... (Imran Ullah Khan) 2793 Sequence title: Heart Resolution: 176x144 Figure 7. Snapshot of “Heart” video sequence, frame 30 Figure 7. Snapshot of “Mobile” video sequence Table 1. Heart Video Sequence Simulation Results For Base Profile and Cabac Enabled Data Rate (Mbps) PSNR(dB) PSNR(dB) SSIM SSIM Base Profile CABAC Enabled Base Profile CABAC Enabled 0 31.9 32.3 0.88 0.88 0.2 37.3 37.6 0.93 0.932 0.5 42 42.4 0.96 0.963 0.8 44.5 45 0.972 0.972 1 45.9 46.5 0.974 0.974 1.2 46.9 47.4 0.974 0.9755 1.5 47.9 48.5 0.976 0.9764 1.8 48.8 49.7 0.977 0.978 2 49.7 50.2 0.979 0.9798 2.2 50.5 50.9 0.98 0.982 2.5 51.1 51.6 0.981 0.984 Table 2. Detail of the Video Sequence Mobile S.No. Detail of Sequence 1 Name Mobile 2 Size CIF (352x288) 3 Total size[byte] 23612683 4 Frames 300 5 Playing time[s] 10.03Min 6 frame size[byte] 79 7 Max frame size[byte] 118449 8 Mean frame size[byte] 78447.45 Table 3. Mobile Video Sequence Simulation Results for Mpeg-4 Video Codec Target bit rate (Kbps) Various Parameter (a)No Control over bit rate (b) Bit Rate Control Offline (c) Bit rate Control Online(with frame skipping) (d) Bit rate Control Online(without frame skipping Average PSNR Y 48.44 34.12 34.55 34.54 100 Average PSNR U 49.78 38.15 38.83 39.12 Average PSNR V 49.88 38.35 38.87 39.41 Bit rate (kb/sec) 98.95 99.5 99.9 99.9 Compression ratio 7:01 95:01:00 95:01:00 95:01:00 Average PSNR Y 44.44 27.85 27.83 27.49 14.4 Average PSNR U 45.78 33.7 34.75 33.68 Average PSNR V 46.36 34.15 35.17 33.95 Bit rate (kb/sec) 1478.3 44 15.7 27 Compression Ratio 7:01 205:01:00 556:01:00 304:01:00
  • 7.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 8, No. 5, October 2018 : 2788 - 2794 2794 Table 4. Comparative Statement for Qp, Mse, Psnr, Cr And Ssim S.No. Quantization Parameter MSE PSNR SSIM Compression Ratio 1. 10 0.32 54.33 0.99 11.5 2. 15 0.51 52.12 0.98 13.3 3. 20 1.82 47.24 0.96 25.4 4. 25 2.99 43.44 0.95 29.3 5. 27 3.42 42.89 0.94 34.6 6. 30 7.991 39.21 0.91 39.7 7. 35 14.78 35.11 0.85 42.4 8. 40 20.71 33.2 0.78 44.0 9. 45 28.62 31.6 0.73 44.9 10. 50 39.12 30.7 0.69 46.1 9. CONCLUSION In this paper H.264 and MPEG-4 basic features are discussed along with how the performance is influenced by rate controller for H.264/AVC and MPEG-4. There are test model VM8 verification model version 8.0 is used for the analysis of H.264/AVC and MPEG-4. In constant bit-rate applications, both on- line and off-line rate control methods gives the obtained bit-rate very close to the target bit rate (TBR) for a moderate target bit rates (medium and high). However, for low bit rate applications only online method results in the actual bit-rate being close to the TBR bit rate. There are many other parameters and functionalities in MPEG-4 which are aimed to be investigated in future. REFERENCES [1] Manjanaik.N, Manjunath.R “Intra Frame Coding for Advanced Video Coding Standard to Control PSNR and Bitrate Using Gaussian Pulse” International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319– 6378, Volume-2, Issue-5, March 2014. [2] T. Bernatin, G. Sundari, B. Gayethri, Swarna Ramesh, “ Performance analysis of Rate Control Scheme in H.264 Video Coding” Indian Journal of Science & Technology, Vol 9(30), Doi:10.17485/ijst/2016/v9i30/99061, August 2016 [3] D.Marpe, T.Wiegand and G.J.Sullivan, “The H.264/MPEG Advance video coding standard and its applications”, IEEE Communications Magazine, vol.44, no.8, pp.134-144, Aug.2006. [4] I. U. Khan, M.A. Ansari “Evaluation of Deblocking Filter for H.263 Video Codec & Proposed Algorithm for Entropy Coding for MPEG-4 Video Codec” has been published in “International Journal of Control Theory and Applications” (No.2 2015). [5] J. Ribas-Conklin, S. Lei. “Rate control in DCT video coding for low-delay communication.IEEE Trans. Circuit Syst. Video Technol. Feb 1999, 9(1):172-185 [6] P.Topiwala, G.sullivan, A.Joch, and F.Kossentini, “Performance evaluation of H.26L, TML8 vs. H.263++ and MPEG-4,”ITU-T Q.6/SG6 (VCEG) Tech. Rep. N8, sept.2001. [7] Hung-Ju Lee, Ya-Qin Zhang. Scalable Rate Control for MPEG-4 Video. IEEE Trans. Circuits 64 and Systems for Video Technology2000, 10(6): 878-894. [8] I. U. Khan, M.A. Ansari “Data Partitioning and MDC for the SPECK Coder for real time applications over wireless channel” has been published in “Indian Journal of Industrial and Applied Mathematics”, Volume 6 , Issue 1,Jan- June (2015) pp. 57 - 72. [9] Liao K-Y, Yang J-F, Sun M-T. Rate-Distortion cost estimation for H.264/AVC. IEEE Transactions on Circuits and System Video Coding Technology. 2010 Jan; 20(1):38–49. [10] Bernatin T, Sundari G. Video compression based on Hybrid transform and quantization with Huffman coding for video code. International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT). 2014 Jul; 4(7):476–80. [11] I. U. Khan, M.A. Ansari,” Overview and Implementation of Intrapredictions for H.264/AVC Video Codec, International Journal of Electronics and Communication Engineering (IJECE) Vol. 3, Issue 4, July 2014, 177-186. [12] M.Ghanbari, “Video Coding: an introduction to standard codes;”IEE press, London 1999. “Video coding for low bit rate communication ITU-T, Recommendation H.263, ver.1, 1995. [13] Xiang Li, Nobert Oertel, Laplace distribution based Lagrangian rate distrortion optimization for hybrid video coding. IEEE Transction on Circuits and Systems. 2009; 19(2): 193-205 [14] James C, Alex Mm, An efficient video codecbased on H.264/AVC standard.IRACST. International Journal of Computer Networks and wireless communications, 2014 Apr;4(2):1-4. [15] Ramu JG, Sathya S Permence evaluation of basic compression methods for different stalellite imaginary, Indan Journal Sci. & Tech. .2015 Aug;8(19): 1-8. [16] Various video sequences http:www.ubvideo.com Date accessed: 01/07/2015.