Satellite image processing is a technique to enhance raw images received from cameras or sensors placed on satellites, space probes and aircrafts or pictures taken in normal day to day life in various applications. The process of creating thematic maps as spatial distribution of particular information. These are structured by Spectral Bands. These have constant density and when they overlap their densities get added. It performs image analysis on multiple scale images and catches the comprehensive information of system for different application. Examples of themes are soil, vegetation, water-depth and air. The supervising of such critical events requires a huge volume of surveillance data and extremely powerful real time processing for infrastructure

1. SEMINAR REPORT ON
SATELLITE IMAGE PROCESSING
GUIDED BY:Er. BHUPEN KANUNGO
SUBMITTED BY:ALOK KUMAR SAMANTARAY
B.Sc in ETC
ROLL NO:-2010ETC040

2. ACKNOWLEDGEMENT
I wish to express my sincere gratitude to respected Principal and MR. PRADEEP
H.O.D of Electronics and Telecommunication Department of BJB
AUTONOMOUS COLLEGE for providing me an opportunity to present my
seminar on “SATELLITE IMAGE PROCESSING”.
My sincere thanks to my project guide Er. BHUPEN KANUNGO of Electronics
and Telecommunication Department, BJB AUTONOMOUS COLLEGE,
Bhubaneswar for guidance and encouragement in carrying out this seminar,
without whom this success couldn‟t be achieved.
Last but not the least I wish to avail myself of this opportunity to express a sense
of gratitude and love to my friends and my beloved parents for their support and
strength.
Thanking you:
ALOK KUMAR SAMANTARAY

3. CONTENTS
I.
II.
III.
IV.
V.
VI.
VII.
VIII.
IX.
X.
XI.
XII.
XIII.
Satellite Image Processing
Satellite Imagery
Remote Sensing
Methodology of Change Detection in Remote Sensing
Image Segmentation
Image Enhancement
Satellite Image Operators
Google Maps
Features of Google Maps
Importance of Satellite View
Applications
Conclusion
References

4. SATELLITE IMAGE PROCESSING
It is a technique to enhance raw images received from cameras or
sensors placed on satellites, space probes and aircrafts or pictures taken in normal
day to day life in various applications. The process of creating thematic maps as
spatial distribution of particular information. These are structured by Spectral
Bands. These have constant density and when they overlap their densities get
added. It performs image analysis on multiple scale images and catches the
comprehensive information of system for different application. Examples of
themes are soil, vegetation, water-depth and air. The supervising of such critical
events requires a huge volume of surveillance data and extremely powerful real
time processing for infrastructure.

5. SATELLITE IMAGERy
Satellite imagery consists of photographs of Earth or other
planets made by means of artificial satellites. Satellite imagery is sometimes
supplemented by Ariel Photography . it is the photograph of ground taken from an
elevated surface. It has a very high resolution. The platform of such photography is
aircraft, balloons, helicopters, rockets ,etc.
The Landsat program is the largest program for acquisition of images of Earth
from space from space started in 1972 by U.S. All satellite images are produced
by NASA and freely available to public.
The resolution of the sensor defines the pixel size and the detail and accuracy.
1. Spatial resolution :It is the area on ground represented by each pixel.
2. Temporal resolution : It tells how often a satellite obtaining imagery of
particular area.
3. Spectral resolution : It is the specific wavelength interval in electromagnetic
spectrum.
4. Radiometric resolution : It tells how the sensor changes brightness of object .
It‟s range is expressed as power of 2^n.
5. View angle resolution: Number of angles at which ground objects are
recorded.

6. Remote sensing
Remote sensors are devices that sense energy from remote location. Remote
sensing is the science of acquiring , processing and interpreting information or data
collected by remote sensors. This technology is very useful to capture condition of
surface ground with high resolution and direct visual assessment suffered regions.
It helps to collect data from dangerous and inaccessible areas. These are wireless
and have no physical contact with the object. Remote sensing image analysis has
been an important research area for last decades. Most of the applications are
performed at single scale. This technique is quite useful to widely capture
condition of surface ground. High resolution optical images , remotely sensed from
earth observation satellites provide the most direct visual assessment of suffered
region. Digital change detection is one of the most popular techniques used in
remote sensing.
Remote sensing is helping a lot in tracking the infrastructures and damages
caused by natural calamities. Like in 2004, Tsunami was assessed by IKONOS and
Quickbird information resources. Visual interpretation of the buildings damage
was found out by using high resolution satellite images. IKONOS is a commercial
Earth observation satellite that is first to collect publicly the available high
resolution imagery at 1-4 metre resolution. It is a 3-axis stabilized spacecraft
developed by Martin . it is one of the most significant developments in the history
of SpaceAge.
Remote sensing is used in X-RAYS, SPACE PROBES( scientific space
exploration event that explores space), MRI i.e. magnetic resonance imaging (used
in medical imaging technique to visualize internal body parts. It provides good
contrast between tissues.)

7. METHODOLOGY FOR CHANGE
DETECTION OF REMOTE SENSING
IMAGE ALGEBRA:
It identifies the amount of change between pre and post event
images. In image differencing the difference between the two images is
calculated by subtracting each pixel in each image. For this technique to
work the second image should be registered to the first so that corresponding
points coincide. The maximum and minimum difference values are +255
and -255.
D(i, j,k)=BV(i,j,k)[1]-BV(i,j,k)[2]+c
where
D(i, j,k ):-change pixel value
BV(i,j,k)[1]:-brightness value at time1
BV(i,j,k)[2]:-brightness value at time2
c:-constant
i:-row index
j:-column index
k:-single band ( it may be any band red, blue, green ,etc.)
Pixel is the smallest unit of any image.

8. IMAGE SEGMENTATION
Image segmentation is the appropriate strategy to acquire image
objects. It divides an image into spatially continuous , disjoint and homogeneous
regions on the basis of homogeneity and these regions are referred to as IOs. It
reduces over segment regions and maintains segmentation result. If images are
degraded by noise it becomes oversegmented so further processing is required .
Image segmentation has algorithm of two steps-sorting and
flooding.
1. The image pixels are sorted in increasing order of their intensities.
2. At the flooding step the pixels are quickly accessed in increasing intensity
order using sorted image and labels are accessed to catchment basins.
Post processing not only reduces oversegment regions but also
maintains structure of segmentation.

9. Image enhancement
Image enhancement techniques improve the quality of an image
as perceived by a human. These techniques are most useful because many satellite
images when examined on a color display give inadequate information for image
interpretation. There is no conscious effort to improve the fidelity of the image
with regard to some ideal form of the image. There exists a wide variety of
techniques for improving image quality. The contrast stretch, density slicing, edge
enhancement, and spatial filtering are the more commonly used techniques. Image
enhancement is attempted after the image is corrected for geometric and
radiometric distortions. Image enhancement methods are applied separately to each
band of a multispectral image. Digital techniques have been found to be most
satisfactory than the photographic technique for image enhancement, because of
the precision and wide variety of digital processes. The principle objective of
enhancement techniques is to process an image so, that the result is more suitable
than the original image for specification application. Image enhancement
techniques are used to increase the signal-to-noise ratio.
Spatial filtering:
A characteristic of remotely sensed images is a parameter called
spatial frequency defined as number of changes in Brightness Value per unit
distance for any particular part of an image. If there are very few changes in
Brightness
Spatial filtering is the process of dividing the image into its constituent
spatial frequencies, and selectively altering certain spatial frequencies to
emphasize some image features.
Contrast:
Contrast generally refers to the difference in luminance or grey level
values in an image and is an important characteristic. It can be defined as the ratio
of the maximum intensity to the minimum intensity over an image.
Image sharpening:
The main aim in image sharpening is to highlight fine detail in the
image, or to enhance detail that has been blurred.

10. APPLICATION
Satellite imaging is prevelant in many consumer apps today. e.g. , Google maps,
Google earth, GPS cars.
It has many application in meteorology, agriculture, geology, bio-diversity,
landscape and warfare. Images can be in visible colors and in other spectra. There
are elevation maps made by radar images.
The real time processing of satellite images on grid architectures could reveal
geographic and environmental information. e.g., soil, vegetation, water-depth and
air.
Pegasus- mapping engine of dataflow. It is an encryption algorithm for satellite
telemetry and data transfer.
Geoeye 1-satellite launched in 2008 has highest resolution .
EROS satellites are light weight, has high resolution and high performance.
EROS A- a high resolution satellite with 1.9 to 1.2 M
launched in Dec 2000.
panchromatic
resolution
EROS B-2nd generation of very high resolution satellite with 70cm resolution
launched on April 2006.
Meteo-sat 2 is a geostationary weather satellite. It has 3 channels of imager visible,
infrared and water vapour.

11. SATELLITE IMAGE OPERATORS
1. Arithmetic operators: Addition, subtraction, multiplication, division, exponent ,
compliment and negation.
2. Spatial transformation: Blurring, sharpening and filtering. This type of operators
3. Edge , line and spot detection performs gradient transformation.
4. Color conversion operator: Transform the image from one color model to
another color model.
5. Geometric transformation: Rotation, scale and wrap.
6. Statistics: Computation of histogram, mean and standard deviation pixel values
of an image.
7. Non-spatial domain transformation: Forward and inverse Fourier transformation.
8. Radiometric transformation: Includes histogram equalization, mean, scaling,
linear scale and threshold based filtering of an image.

12. IKONOS
3-D SYDNEY OLYMPIC PARK

13. SATELLITE IMAGERY

14. GOOGLE MAPS
Google maps is a web mapping service application and technology
provided by google that powers many map based services. They provide high
resolution aerial or satellite images for most urban areas all over the world. Google
maps satellite images are several months or years old.

15. Google Maps provide route planner under “Get Direction” that
provides upto 4 modes of transportation depending on the area: driving, public
transit, walking and cycling.
Google maps uses JavaScript and it is used in mobiles for various
application. These are being used increasingly for navigation purpose. It helps in
GPS service. My location is used for determining current location. It works in
various platforms:
1.
2.
3.
4.
5.
6.
Android
iOS
Playstation
Blackberry
Nokia
PalmOS
Google collates business listings from multiple on-line and off-line
sources. It reduces duplication in the index. It combines listings automatically
based on address, phone number, or geocode.
Comparable services are:
1.
2.
3.
4.
5.
Apple Maps
Bing Maps
Nokia Maps
Yahoo! Maps
MapQuest

16. This app has a „Download Map Area‟ which enables the user to download the
basic road map. It can download upto 26 sq.km from the spot. It helps to find
out the location of any spot or distance between to spots.This software plots the
streets in blue that are available with yellow icon and green circle around
estimated range of cell site.

17. Features of Google Maps
1.
2.
3.
4.
5.
Search in plain English
Search by voice
Traffic view
Satellite view
Street view
IMPORTANCE OF SATELLITE VIEW IN
GOOGLE MAPS
1. Various governments have complained that the terrorist attacks are planned
using satellite images so Google has blurred some areas for security like U.S.Naval
Base and White House.
2. According to 2012 survey it has provided voice guidance and live traffic
information in cities of Bengaluru, Mumbai, New Delhi, Chennai, Pune and
Hyderabad.

18. CONCLUSION
Satellite image processing has a good application in future and can be used for
analysis of various images taken from satellites and air crafts of ground. It uses
sensors and also accesses various dangerous locations with quality resolution.
Google has also invented Google Maps that can help to view images at various
angles and get the 3-D view of any place on the ground. It can capture an area
around the spot upto a large extend.

19. References
1. en.wikipedia.org/wiki/satellite imagery
2. en.wikipedia.org/wiki/digital globe
3. en.wikipedia.org/wiki/google maps
4. digital image processing IEEE Computer Society