CS60052: Advanced Digital Image Processing And Computer Vision
| CS60052 | |||||||||||||||||||||||||
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| Course name | Advanced Digital Image Processing And Computer Vision | ||||||||||||||||||||||||
| Offered by | Computer Science & Engineering | ||||||||||||||||||||||||
| Credits | 3 | ||||||||||||||||||||||||
| L-T-P | 3-0-0 | ||||||||||||||||||||||||
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| Semester | Spring | ||||||||||||||||||||||||
Syllabus[edit | edit source]
Prerequisites - CS21001: Discrete Structures
Syllabus mentioned in ERP[edit | edit source]
Sensor and Imaging: Imaging Optics, Radiometry of Imaging, Illumination sources and techniques, Camera Principles, Color Imaging, Single Sensor Color Imaging and Color Demosaicing, Range Images, 3D Imaging. Signal Representation: Vector Space and Unitary Transforms, Multi-Resolutional Signal Representation, Wavelet Decomposition, Scale space and diffusion, Representation of color, Retinex Processing, Markov Random Field Modeling of Images. Non-linear Image Processing: Median and Order Statistics Filters, Rank-Ordered-Mean Filters and Signal Dependent Rank-Ordered-Mean Filters, Two Dimensional Teager Filters, Applications of nonlinear filters in image enhancement, edge detections, noise removal etc. Feature Estimation: Morphological Operations, Edge Detection, Edges in multichannel images, Texture Analysis, Optical flow based motion estimation, Reflectance based shape recovery, Depth from focus, Stereo matching and depth estimation. Image and Video Compression Standards: Lossy and lossless compression schemes: Transform Based, Sub-band Decomposition, Entropy Encoding, JPEG, JPEG2000, MPEG-1, MPEG-4, and MPEG-7. Object Analysis, Classification: Bayesian Classi-fication, Fuzzy Classification, Neural Network Classifiers, Shape Reconstruction from volumetric data, knowledge-based interpretation of images.