Contact Hours and Credits : ( 3 -0- 0 ) 3
To treat the 2D systems as an extension of 1D system design and discuss techniques specific to 2D systems.
Linearity and space-invariance. PSF, Discrete images and image transforms, 2-D sampling and reconstruction, Image quantization, 2-D transforms and properties.
Image enhancement- Histogram modelling, equalization and modification. Image smoothing , Image crispening. Spatial filtering, Replication and zooming, Generalized cepstrum and homo morphic filtering.
Image restoration- image observation models. Inverse and Wiener filtering. Filtering using image transforms. Constrained least-squares restoration. Generalized inverse, SVD and interactive methods. Recursive filtering. Maximum entropy restoration. Bayesian methods.
Image data compression-sub sampling, Coarse quantization and frame repetition. Pixel coding - PCM, entropy coding, run length coding Bit-plane coding. Predictive coding. Transform coding of images. Hybrid coding and vector DPCM. Inter frame hybrid coding.
Image analysis- applications, Spatial and transform features. Edge detection, boundary extraction, AR models and region representation. Moments as features. Image structure. Morphological operations and transforms. Texture. Scene matching and detection. Segmentation and classification
Students are able to