1 February 1998 Local adaptive filtering in transform domain for image restoration, enhancement, and target location
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Abstract
Local adaptive linear filters for image restoration were reported by the present author on one of the previous Wien workshops on image processing and computer graphics. The filters work in the domain of an orthogonal transform in a moving window and nonlinearly modify the transform coefficients to obtain an estimate of the central pixel of the window.In the present paper, we suggest an extension of local adaptive filtering in the domain of DFT/DCT to the processing multicomponent images, describe a recursive algorithm for local 3D DCT spectrum analysis which permits to substantially reduce the computational complexity of the filtering, present experimental result in denoising, enhancement and deblurring monochrome and color images and in target location in stereoscopic images. We also discuss using other than DCT orthogonal and color images and in target localization in stereoscopic images. We also discuss using other than DCT orthogonal transforms such as Walsh- Hadamard and Haar transforms and show that, for the window size 3 X 3 pixels, filtering in transform domain can be carried out in a form of 5 channel convolution with masks implementing local mean and 4 directional Laplacians: horizontal, vertical and two diagonal.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonid P. Yaroslavsky, Leonid P. Yaroslavsky, } "Local adaptive filtering in transform domain for image restoration, enhancement, and target location", Proc. SPIE 3346, Sixth International Workshop on Digital Image Processing and Computer Graphics: Applications in Humanities and Natural Sciences, (1 February 1998); doi: 10.1117/12.301362; https://doi.org/10.1117/12.301362
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