Elements of Visual perception. Image sensing and Acquisition . Imaging in different bands. Digital Image Representation. Relationship between pixels. Image transformations: 2D-DFT, DCT, DST, Hadamard, Walsh, Hotelling transformation, 2D-Wavelet transformation, Wavelet packets.
Image Enhancements in spatial domain and Frequency domain. Image Restoration techniques. Color Image processing.
Error free compression: Variable length coding, LZW, Bit-plane coding, Lossless predictive coding Lossy compression: Lossy predictive coding, transform coding, wavelet coding. Image compression standards, CCITT, JPEG, JPEG 2000, Video compression standards.
Summary of morphological operations in Binary and Gray Images. Image segmentation: Point, Line and Edge segmentation. Edge linking and Boundary detection. Segmentation using thresholding, Region based segmentation. Segmentation by morphological watersheds. Use of motion in segmentation.
Feature Extraction from the Image: Boundary descriptors, Regional descriptors, Relational descriptors.
1. R. C.Gonzalez, R.E.Woods,” Digital Image processing”, Pearson edition, Inc3/e,2008.
2. A.K.Jain,” Fundamentals of Digital Image Processing”, PHI,1995
1. J.C. Russ,” The Image Processing Handbook”, (5/e), CRC, 2006
2. R.C.Gonzalez & R.E. Woods; “Digital Image Processing with MATLAB”, Prentice Hall, 2003
Students are able to
CO1: understand the need for image transforms different types of image transforms and their properties.
CO2: develop any image processing application.
CO3: understand the rapid advances in Machine vision.
CO4: learn different techniques employed for the enhancement of images.
CO5: learn different causes for image degradation and overview of image restoration techniques.
CO6: understand the need for image compression and to learn the spatial and frequency domain techniques of image compression.
CO7: learn different feature extraction techniques for image analysis and recognition
