Global and Sliding-Window Transform Methods in Image Processing: Restoration, Resampling, and Target Location
Prof. Leonid Yaroslavsky, Dept. of Interdisciplinary Studies, Tel Aviv University, Israel

Seminar • 19 May 2003

More Info ...Abstract
Any signal processing is a process carried out in the domain of a certain integral signal transform. In digital processing, it is the set of coefficients of signals representation over selected transform basis functions that are subject of modification in the processing. The selection of the transform is governed, depending of application, by such transform features as signal energy compaction capability, computational complexity, the ease of global/local adaptivity, the appropriateness to the processing task. In this talk, global and sliding window transform domain methods for image processing are reviewed for such applications as image restoration, image resampling, and target location. For image restoration (blind denoising/deblurring), sliding window DCT (SWDCT) domain adaptive filters and hybrid SWDCT/wavelet filters are advocated as a tool for multi component and space variant image deblurring and edge preserving denoising. For image resampling, global and sliding window DCT domain methods are described. Global DCT domain method is capable of boundary effect free signal regular resampling with arbitrary interpolation kernels including that of discrete sinc- interpolation. SWDCT method is applicable for arbitrary irregular signal resampling with simultaneous signal restoration. It is also well suited for local adaptive resampling with adaptation of the interpolation kernel to signal local features. For target location, global and sliding window DFT/DCT transform methods are described that implement optimal adaptive correlator for reliable target location in single and multi-component images with heavily cluttered background.