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SEMI NAR REPORT ON SATELLITE IMAGE PROCESSING GUIDED BY:- Er. BHUPEN KANUNGO SUBMITTED BY:-

Satellite image Processing Seminar Report

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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

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Page 1: Satellite image Processing Seminar Report

SEMINAR REPORT ON

SATELLITE IMAGE PROCESSING

GUIDED BY:-

Er. BHUPEN KANUNGO

SUBMITTED BY:-

ALOK KUMAR SAMANTARAY

B.Sc in ETC

ROLL NO:-2010ETC040

Page 2: Satellite image Processing Seminar Report

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

CONTENTS

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I. Satellite Image ProcessingII. Satellite Imagery

III. Remote SensingIV. Methodology of Change Detection in Remote SensingV. Image Segmentation

VI. Image EnhancementVII. Satellite Image Operators

VIII. Google MapsIX. Features of Google MapsX. Importance of Satellite View

XI. ApplicationsXII. Conclusion

XIII. References

SATELLITE IMAGE PROCESSING

Page 4: Satellite image Processing Seminar Report

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.

SATELLITE IMAGERy

Page 5: Satellite image Processing Seminar Report

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.

Remote sensing

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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.)

METHODOLOGY FOR CHANGE DETECTION OF REMOTE

SENSING

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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.

IMAGE SEGMENTATION

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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.

Image enhancement

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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 BrightnessSpatial filtering is the process of dividing the image into its constituentspatial frequencies, and selectively altering certain spatial frequencies toemphasize 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 ratioof 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.

APPLICATION

Page 10: Satellite image Processing Seminar Report

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 panchromatic resolution launched in Dec 2000.

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.

SATELLITE IMAGE OPERATORS

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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.

IKONOS

3-D SYDNEY OLYMPIC PARK

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GOOGLE MAPS

Page 14: Satellite image Processing Seminar Report

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.

Page 15: Satellite image Processing Seminar Report

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. Android2. iOS3. Playstation4. Blackberry5. Nokia6. 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. Apple Maps2. Bing Maps3. Nokia Maps4. Yahoo! Maps5. MapQuest

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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.

Features of Google Maps

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1. Search in plain English2. Search by voice3. Traffic view4. Satellite view5. 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.

CONCLUSION

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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.

References

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1. en.wikipedia.org/wiki/satellite imagery2. en.wikipedia.org/wiki/digital globe3. en.wikipedia.org/wiki/google maps4. digital image processing IEEE Computer Society