Digital Image Processing

Course No.: EE 605

Course Title: Digital Image Processing

Offerings (Internal Site for Students Enrolled in the Course) : Semester 1 (2018-19) , Semester 1 (2017-18) , Semester 1 (2016-17) , Semester 1 (2015-17)

Credits: L-T-P-C: 3-0-0-4

Prerequisites: Exposure to basic mathematics: calculus, linear algebra and probability (MA 101, MA 102, MA 201, MA 202 or their equivalent), and a basic knowledge of programming

Description:

This elective course is primarily targeted towards electrical engineering and computer science graduate students which could be taken as an elective by advanced UG students as well. Good programming skills in MATLAB/Phython/C will be helpful.

This is aimed at understanding the process of image formation, representation and commonly used techniques for enhancement, restoration, compression, and analysis of images.

Course contents:

Fundamentals – Visual perception, image sensing and acquisition, image sampling and quantization; Intensity transformations – nonlinear transformations for enhancement, histogram equalization; Spatial filtering – convolution, linear and order statistic filters, unsharp masking. Image Transforms – discrete Fourier transform, discrete cosine transform; Frequency domain filtering – DFT, image smoothing, specialized filters (Gaussian, Laplacian, etc); Image restoration – using spatial filters, Wiener filter; Introduction to color spaces and color image processing; Morphological image processing – erosion and dilation, opening and closing, hit-or-miss transform, thinning and shape decomposition; Image segmentation – edge detection, thresholding, region-based segmentation, watershed algorithm; Image compression – fundamentals, lossless coding, predictive coding, transform coding.

* The list of books provided here is not exhaustive as many of the topics will be covered from multiple sources including some high impact research papers. Pointers to these sources will be provided from time to time during the lectures.

^* Matlab/Phython/C use is required for this course.

Textbooks:

• Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", 3^rd Edition Prentice-Hall, 2008

References:

• Rafael C. Gonzalez, Richard E. Woods, and S. L. Eddins, ``Digital Image Processing Using MATLAB,'' Prentice Hall, 2004. ISBN 0130085197
• A. K. Jain, "Fundamental of Digital Image Processing," Prentice-Hall, 1996
• W. K. Pratt, "Digital Image Processing", 3^rd Edition, Wiley, 2001
• Al Bovik editor, "Handbook of Image & Video Processing", ISBN 0-12-119790-5, Academic Press, San Diego, 2000