Two-Dimensional Signals and Systems: Two-dimensional convolution, 2D Discrete-Space Fourier Transform, Inverse 2-D Fourier Transform, Fourier Transform of 2-D or Spatial Convolution, Symmetry properties of Fourier Transform, Continuous-Space Fourier Transform. Sampling in two dimensions: Sampling theorem, Change in Sample rate, Down sampling, Ideal decimation, Up sampling, Ideal interpolation. Continuous Image characterization: Psychophysical vision properties, Photometry, Colorimetry. Fundamentals of Digital Image Processing: Image acquisition – Various modalities, Image sampling and quantization, mathematical representation, Image reconstruction based on interpolation. Gray level transformation, Histogram processing, Arithmetic and logic operations. Transform and filtering: Intensity transformation and spatial filtering, filtering in frequency domain, Image restoration and reconstruction, Binary image morphology. Smoothing and sharpening filters, Line detection, Edge detection, Zero crossings of the second derivative. DFT, smoothing in frequency domain filtering, Sharpening in frequency domain filtering.
Degradation model, noise models, restoration in spatial domain, restoration in frequency domain. Estimation of degradation function, inverse filtering, Wiener filtering, constrained least square filtering. Color Image Processing: Color Models, the RGB Color Model, the CMY and CMYK Color Models, the HSI Color Model, Pseudo color image processing, Basics of Full Color Image Processing, Smoothing and Sharpening, Image Segmentation Based on Color. Image Segmentation-Point, Line, and Edge Detection, Thresholding-Types Boundary based and Region-Based Segmentation. Representation of Boundary Descriptors, Regional Descriptors- Texture descriptors. MATLAB applications.