Image Processing Syllabus for NIT Jalandhar
EC-453 Image Processing [3 0 0 3]
Image representation – Gray scale and colour Images, image sampling and quantization
Two dimensional orthogonal transforms – DFT, FFT, WHT, Haar transform, KLT, DCT
Image enhancement – filters in spatial and frequency domains, histogram-based processing, homomorphic filtering.
Edge detection – non parametric and model based approaches, LOG filters, localisation problem
Image Restoration- PSF, circulant and block- circulant matrices, deconvolution, restoration using inverse filtering, Wiener filtering and maximum entropy-based methods.
Mathematical morphology – binary morphology, dilation, erosion, opening and closing, duality relations, gray scale morphology, applications such as hit-and-miss transform, thinning and shape decomposition.
Computer tomography – parallel beam projection, Radon transform, and its inverse, Back-projection operator, Fourier-slice theorem, CBP and FBP methods, ART, Fan beam projection.
Image communication – JPEG, MPEGs and H.26x standards, packet video, error concealment.
Image texture analysis – co-occurence matrix, measures of textures, statistical models for textures.
Hough Transform, boundary detection, chain coding, and segmentation, thresholding methods.
1. Gonzalez, Woods, “Digital Image Processing”, Pearson Education Asia, Ninth Indian Reprint,
2. Arthur R. Weeks, Jr, “Fundamental of Electronic Image Processing”, Prentice Hall of India, (2003).
3. Anil K Jain, “Fundamental of Digital Image Processing”, Prentice Hall of India, (2001).
4. Ioannis Pitas, “Digital Image Processing Algorithms and Applications”, Wiley-Interscience. 2000.
5. A. Rosenfold and A.C. Kak, Digital Image Processing, Vol1 and 2 , PHI
6. H.C. Andrew and B.R.Hunt, Digital Image Retoration, PHI