EC 803D-Digital Image Processing |
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Introduction, image definition and its representation, neighborhood, Image capturing techniques.
Orthogonal transformations like DFT , DCT , Wavelet
Enhancement / Restoration: contrast enhancement, multi-scals / multi-resolution enhancement
Smoothing and sharpening, least square restoration, constrained least square restoration, Wiener
filter.
Segmentation: pixel classification, global/local gray level thresholding, region growing,
split/merge techniques, model based – Facet model, edge detection operators, Hough transform.
Image feature/primitive extraction, component labeling, medial axis transform,
skeletonization/ thinning,shape properties, textural features-moments, gray level co-occurrence
matrix, structural features, fourier descriptor, polygonal approximation.
Compression: coding, quantization, spatial and transform domain based compression.
Color image processing: color model, enhancement, and aegmentation.
Content-based image retrieval.
Few applications of image processing,
Assignment
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Text Books: |
1. R.C. Gonzalez and R.E. Woods, Digital Image Processing, Pearson Education Asia, 2004
2. Anil k Jain, Fundamentals of Digital Picture Processing, Prentice Hall
India, 1998.
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Reference Books: |
3. M. Sonaka, V. Hlavac and R. Boyle,Image Processing Analysis and Machine
Vision, PWS Publishing, 1999.
4. S.K. Pal, A.Ghosh, and M.K. Kundu, Soft Computing for Image Processing, Physica
Verlag, (Springer), Heidelberg,1999.
5. D. Salnmon, Data Compression: The Complete References, Springer Verlag, 2004.
Prentice Hall of India, 1997.
6. R. M. Haralick and L. G. Shspiro, Computer and Robot Vision, Vol. 1 & 2, Addison-
Wesley, 1992.
7. N. S. Kopeika, A system Engineering Approach to Imaging, Prentice Hall of India, 2003
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