School of Engineering and Technology, (SET)  
 
Semester Offering: January
 
AT76.09 : Digital Image Processing in Remote Sensing  3(2-3) [Elective course]
Course objectives:

This course will provide students with more techniques in digital image processing for remote sensing data analysis adding to AT76.03 Remote Sensing. This course emphasizes on implementation of algorithms as computer programs. The techniques taught in this course have application in several fields dealing with image data.

 
Learning Outcomes:

Review of C Language. Image Data Handling in Computer System. Remote Sensing Image Files Format and Handling. Image Processing Algorithm and Implementation I(Basic Algorithm) & II (Application). RS data and DEM for 3D Visualization and Mapping. Laboratory Session.

 
Pre-requisite(s):

None

 
Course Outline:

I.       Review of C Language
1.        Syntax
2.        Functions
3.        Control Structures
4.        Pointer and Array
5.        Dynamic Memory Allocation
6.        File I/O

II.     Image Data Handling in Computer System
1.        Memory System
2.        Image Model in Computer Memory
3.        Memory Allocation
4.        Handling of Various Types & Length of Image
5.        File System
6.        File Format: Basic
7.        Image File Handling Subroutines

III.    Remote Sensing Image File Format and Handling
1.        Tagged Image File Format (TIFF)
2.        Joint Photographic Experts Group (JPEG)
3.        Hierarchical Data Format (HDF)
4.        Image File Format used in Commercial Remote Sensing Software such as
ENVI, ER-MAPPER, ARC/INFO, and etc.

IV.    Image Processing Algorithm and Implementation-I (Basic Algorithm)
1.        Image Statistics
2.        Image Contrast Enhancement
3.        Color Composite
4.        Pseudo Color Composite
5.        Image Filtering
6.        Image matching

V.     Image Processing Algorithm and Implementation –II (Application)
1.        Image Geometric Conversion - Resampling
2.        River Network Extraction
3.        Handling of Huge Image Files
4.        Image Classification
5.        Fast Fourier Transform
6.        Texture Analysis
7.        Segmentation

VI.    RS data and DEM for 3D Visualization and Mapping
1.        DEM (Digital Elevation Model)
2.        Coordinate System
3.        Shading Model
4.        Z-Buffer Model
5.        Topographic feature extraction
6.        Real-time mapping techniques

VII. Laboratory Session
1.        C development environment on Windows and LINUX
2.        Exercise of Basic C Programming
3.        Using Image Handling Libraries
4.        Reading / Writing Image Files
5.        Implementation of Image Processing Algorithm –I (Basic Algorithm)
6.        Implementation of Image Processing Algorithm –II (Application)
7.        3D Image Creation and publishing on Web

 
Laboratory Sessions:
1.        C development environment on Windows and LINUX
2.        Exercise of Basic C Programming
3.        Using Image Handling Libraries
4.        Reading / Writing Image Files
5.        Implementation of Image Processing Algorithm –I (Basic Algorithm)
6.        Implementation of Image Processing Algorithm –II (Application)
7.        3D Image Creation and publishing on Web

 
Learning Resources:

Textbook:

Lecture notes

 
Reference Books:
Brian Overland:
         C in Plain English, MIS Press, 1995

R.C. Gonzales, R. E. Woods:
         Digital Image Processing (2nd Edition), Prentice Hall, 2002, ISBN: 0201180758

J. C. Russ:
         The Image Processing Handbook, Fourth Edition., CRC Press, 2002

 
Evaluation Scheme:

Final grades will be computed according to the following percentage distribution:

Mid-semester Examination 30%
Final Examination 40%
Assignments/Lab Assignments/Mini Project 30%.

Examination will be closed book