MSc (Mathematics and Computing) Programme:Digital Image ProcessingThapar University
Price on request
Introduction and Digital Image Fundamentals: Digital Image Representation, Fundamental steps in Image Processing, Elements of Digital image processing systems, Sampling and quantization, neighbors of a pixel, adjacency, connectivity, Regions and Boundaries, Distance measures, Image operations on a pixels basis, Linear and Non linear operations
Image Enhancement in the Spatial domain: Gray level transforms, Histogram Processing, Enhancement using Arithmetic/Logic Operations, smoothing and sharpening filters
Image Enhancement in the Frequency domain: 1-D and 2-D Fourier Transform and their Inverse, Filtering, Smoothing and sharpening domain filters, Homomorphic Filtering
Image Restoration: Degradation Model, Noise models, Restoration in the presence of Noise only spatial filtering, Periodic Noise reduction by frequency domain filtering, Estimating the degradation function
Color Image Processing: Color models, Pseudocolor Image Processing, Color Transforms, Smoothing and sharpening, Color Segmentation, Noise in color images, Color Image compression
Image Compression: Fundamentals, Compression Models, Error free Comparison, Lossy Compression, wavelets in Image compression, Image compression standards.
Morphological Image Processing: Dilation and Erosion, Basic Morphological algorithms, Extension to gray scale images.
Image Segmentation: Detection of discontinuities, Edge linking and boundary detection, Thresholding, Region oriented Segmentation, Motion based Segmentation.
Representation and Description: Representation schemes, Boundary description, Regional descriptors, Morphology.
Object Recognition: Patterns and Pattern classes, Decision Theoretic Methods, Structural methods.
Laboratory work: The lab work will be based on operations on images. The programs will be based on image enhancement, image zooming, image cropping, image restoration, image compression, image segmentation and applications.