22913 Image Processing
Credits: 4 graduate credits in Computer Science
Prerequisite: Admission to the graduate program in Computer Science 1
The course is based on chapters from Digital Image Processing (3rd ed.), by R.C. Gonzalez and R.E. Woods (Prentice Hall, 2008); and from A Simplified Approach to Image Processing, by R. Crane (Prentice Hall, 1997).
Image processing is an application of computer science that deals with digital image and video processing. Students study the theoretical and practical foundations required for computer image processing and analysis. The course is accompanied by the MATLAB software package for image and signal processing. Previous knowledge of MATLAB is not required.
Topics: Representation of digital images on the computer – basic concepts, grayscale image representation, color images and color models, binary image; Image enhancement – discrete Fourier transform, uses of FFT for image enhancement (sharpening, smoothing, deblurring, reducing cyclical interference), convolution and correlation and their relationship to Fourier transform, KLT transform; Image restoration – grayscale histograms, contrast and brightness, filters for removing noise, smoothing, sharpening and edge detection, filter analysis using Fourier analysis; Geometric operations on images, warping and morphing – interpolation using convolution, image enlargement, image reduction, image transformations, morphing; Image compression – basic concepts of information theory, image compression models, use of FFT and DCT for image compression, image compression standards; Video – video capture and compression, movement prediction, and video compression standards.
1Students who have not fulfilled this requirement may, under certain circumstances, enroll in this course.