3 Credit Hour Course
Intended For Level 0 Term 0 Students
Prerequisite:
Image sampling and quantization; Image smoothing , sharpening and contrast enhancement in spatial and frequency domains: basic gray level transformation, histogram processing, image subtraction, image averaging, Gaussian and Laplacian filters in spatial and frequency domains, convolution theorem; Image de-noising: noise models, noise reduction by spatial and frequency domain filters, mean filter, adaptive filter, bandpass and band reject filters, notch filter, inverse filter, minimum mean square error filter; Multi-resolution image processing: wavelet transform in one and two dimensions, tree structured wavelet transform, pyramid structured wavelet transform, curvelet transform; Morphological image processing: erosion, dilation, opening, closing, hole filling, connected components, thinning, skeletons, extension of morphological operations to gray scale images; Image segmentation: thresholding, region based segmentation, contour based segmentation, graph based segmentation; Color image processing: color models and transformations, edge detection and segmentation in color images, color image compression; Digital image security; Image content feature extraction, representation and image retrieval; Concept learning and object recognition.
