Digital Signal and Image Processing

Two-Dimensional Signals and Systems, Separable Signals, Periodic Signals, General Periodicity, 2-D Discrete-Space Systems, 2-D Convolution, Stability in 2-D Systems. Digital Image Fundamentals-Image acquisition, pixel representation, sampling quantization.

Image enhancement in spatial domain-linear and non linear operators, basic gray level transforms, Histogram, histogram processing- equalization, Matching & color histogram. Enhancement using arithmetic/logic operations, spatial filtering, smoothing spatial filtering, Sharpening spatial filtering. Discrete Fourier Series, Properties, Periodic Convolution, Shifting Property, DFT, Circular Convolution and Shift, Interpolating DFT- 1D and 2D Discrete Cosine Transform, Sub-bands and Discrete Wavelet Transform and relation to filter banks Smoothing frequency domain filtering, sharpening frequency domain Image Transforms --Morphological Image processing- restoration- Sparse representation in image processing. Color Image Processing:

Segmentation - Thresholding – Edge-Based Segmentation – Region Based Segmentation Mean Shift – Active Contour Models – Geometric Deformable Models – Fuzzy Connectivity – 3D Graph Based Image Segmentation – Graph Cut Segmentation - Optimal Surface segmentation- Shape Representation and Description: Hough Transform – Feature Detection and matching - Contour Based and Region Based Shape representation and Description – Feature descriptors- SIFT,SURF,GLOH-matching and tracking Motion Estimation Optical Flow Segmentation - Recognition(Applications as Case studies).