CS 663 - Fundamentals of Digital Image Processing

Course content

Image enhancement: histogram equalization and specification, contrast modification, neighborhood filtering, image smoothing and image sharpening. Frequency domain processing: Sampling theorem, Fourier transforms and their properties, applications in image filtering Edge detection Principal components analysis: applications in face recognition [eigenfaces], and denoising (later) Image restoration: denoising, deblurring Image segmentation: region-based methods, template matching, Hough transform, Mean shift, active contours (snakes) Color models, filtering of color images Image compression: JPEG, wavelet representation for images Tomography, radon Transform, projection theorem, image reconstruction from back-projections Statistics of natural images (time permitting), Morphological image processing (time permitting), Sparse representations and non-local similarity (time permitting), introduction to compressive sensing (time permitting)

Total credits : 6 - Lecture and Tutorial
Type : Department Elective
Duration : Full Semester
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