this presentation based on the image processing and its one of the process that is image compression.

1. BY ASHWINI AWATARE

2. Contents:-
What is Image Processing ?
Steps followed in Image Processing .
Purpose of Image Processing.
Types of Image Processing
Applications of Image Processing
Advantage and Limitations .
Image Compression
Goals of Image Compression .
Flow of Image Compression.
Approaches
Models

3. What is Image Processing
Image processing is a method to convert an image
into digital form and perform some operations on it, in
order to get an enhanced image or to extract some
useful information from it.
Usually Image Processing system includes treating
images as two dimensional signals while applying
already set signal processing methods to them.

4. Image Processing :
An image defined in the "real world" is considered to be
a function of two real variables say x , y.
 Before going to processing an image, it is converted into
a digital form. Digitization includes sampling of image
and quantization of sampled values.
 After converting the image into bit information, processing
is performed.
 This processing technique may be,
*Image enhancement
* Image reconstruction
* Image compression

5. Image enhancement refers to accentuation, or
sharpening, of image features such as boundaries.
Image restoration is concerned with filtering the
observed image to minimize the effect of
degradations.
Image compression is concerned with minimizing the
number of bits required to represent an image.
* Text compression - CCITT GROUP3 & GROUP4
* Still image compression - JPEG
* Video image compression -MPEG

6. Image processing basically includes
the following three steps.
 Importing the image with optical scanner or by digital
photography.
Analyzing and manipulating the image which includes
data compression and image enhancement and
spotting patterns that are not to human eyes like
satellite photographs.
 Output is the last stage in which result can be altered
image or report that is based on image analysis.

7. Modern digital technology has made it possible to
manipulate multi-dimensional signals with systems
that range from simple digital circuits to advanced
parallel computers. The goal of this manipulation can
be divided into three categories:
* Image Processing image in -> image out
* Image Analysis image in -> measurements out
* Image Understanding image in -> high-level
description out
Image processing is referred to processing of a 2D
picture by a computer.

9. Purpose of Image processing
The purpose of image processing is divided into 5 groups.
They are:
 Visualization - Observe the objects that are not visible.
 Image sharpening and restoration - To create a better
image.
 Image retrieval - Seek for the image of interest.
 Measurement of pattern – Measures various objects in
an image.
 Image Recognition – Distinguish the objects in an
image.

10. Types of Image Processing
 There are two types of the Image Processing
1> Analog Image Processing
Analog Image Processing refers to the
alteration of image through electrical means.
The most common example is the television
image.

11. 2>Digital Image Processing :
In this case, digital computers are used to
process the image.
 The image will be converted to digital form using a
scanner – digitizer and then process it.
 It is defined as the subjecting numerical
representations of objects to a series of operations in
order to obtain a
desired result

12. Applications :
Computer Vision
Agricultural Applications
Face Detection
Medical Imaging
Microscope Image Processing
Raster Operation
Remote Sensing
 Non-destructive Evaluation

13. Applications
 Forensic Studies
 Textiles
 Material Science.
 Military
 Film industry
 Document processing
 Graphic arts
 Printing Industry

14. Advantage
Advantages are as follows :
 you can remove unwanted objects, adjust exposure,
saturation, hue, levels, sharpness, and more.
Easy to manipulate.
 Compact storage.

15. Limitations :-
Limitations are as follows:
It's very costly depending on the system used, the
number of detectors purchased.
 Time consuming
 Lack of qualified professional

16. Image Compression :-
The objective of image compression is to reduce
irrelevance and redundancy of the image data in order
to be able to store or transmit data in an efficient form.
Image compression is minimizing the size in bytes of a
graphics file without degrading the quality of the
image to an unacceptable level. The reduction in file
size allows more images to be stored in a given amount
of disk or memory space

17.  It also reduces the time required for images to be sent
over the Internet or downloaded from Web pages.
There are several different ways in which image files
can be compressed. For Internet use, the two most
common compressed graphic image formats are
the JPEG format and the GIF format. The JPEG
method is more often used for photographs, while the
GIF method is commonly used for line art and other
images in which geometric shapes are relatively
simple.

18. The JPEG standard specifies the codec, which defines
how an image is compressed into a stream of bytes and
decompressed back into an image, but not the file
format used to contain that stream.
The Exif and JFIF standards define the commonly used
file formats for interchange of JPEG-compressed
images.

19. Goal of Image Compression
 The goal of image compression is to reduce the
amount of data required to represent a digital image.

20. The Flow of Image Compression
 What is the so-called image compression coding?
 To store the image into bit-stream as compact as possible
and to display the decoded image in the monitor as exact
as possible

21. Flow of compression
The image file is converted into a series of binary data,
which is called the bit-stream
The decoder receives the encoded bit-stream and decodes it
to reconstruct the image
The total data quantity of the bit-stream is less than the
total data quantity of the original image
Original Image Decoded Image
Bitstream
Encoder 0101100111... Decoder

22. Approaches
 Lossless
 Information preserving
 Low compression ratios
 Lossy
 Not information preserving
 High compression ratios

23. Definitions: Compression Ratio
compression
Compression ratio:

24. Image Compression Model

25. Image Compression Model
 Mapper: transforms input data in a way that facilitates
reduction of interpixel redundancies.

26. Image Compression Model

 Quantizer: reduces the accuracy of the mapper’s
output in accordance with some pre-established fidelity
criteria.

27. Image Compression Model

 Symbol encoder: assigns the shortest code to the most
frequently occurring output values.

28. Image Compression Models
 Inverse steps are performed.
 Note that quantization is irreversible in general.

29. Sources :
 http://www.noupe.com/design/everything-you-need-to-
know-about-image-compression.html
http://en.wikipedia.org/wiki/Image_processing
 http://en.wikipedia.org/wiki/Image_compression
http://whatis.techtarget.com/definition/image-compression
http://www.html5rocks.com/en/tutorials/speed/img-compression/
http://docs.gimp.org/en/gimp-tutorial-quickie-jpeg.
html // jpeg image compression .

30. THANK YOU