Course Contents

Brief Introduction to MATLAB Digital image fundamentals: representation, sampling and quantization, image acquisition, basic relationships between pixels, imaging geometry. Image transforms: discrete Fourier transform, discrete cosine transform, Hotelling transform. Image enhancement: in spatial domain and in frequency domain, image smoothing and sharpening, image interpolation. Image restoration: degradation models, inverse filter, Wiener filter, Color image processing. Image segmentation: detection of discontinuities, thresh holding, region-oriented segmentation, the use of motion analysis in segmentation. Image registration and object recognition. Wavelets. Morphological operations.

Course Learning Outcomes

Understand the basic aspects of digital image representation and their practical implications , Have the ability to design point-wise intensity transformations to meet stated specifications, Understand 2-D convolution, the 2-D DFT, and have the ability to design systems using these concepts, Have a command of basic image restoration techniques, Understand the role of alternative color spaces, and the design requirements leading to choices of color space , Appreciate the utility of wavelet decomposition and their role in image processing systems, Evaluate the performance of different image processing algorithms