Regularization of rif blind image deconvolution (0).

Content Provider	CiteSeerX
Author	Robert, Michael Ng Plemmons, Robert J. Qiao, Sanzheng
Abstract	Blind restoration is the process of estimating both the true image and the blur from the degraded image, using only partial information about degradation sources and the imaging system. Our main interest concerns optical image enhancement, where the degradation often involves a convolution process. We provide a method to incorporate truncated eigenvalue and total variation regularization into a nonlinear recursive inverse filter (RIF) blind deconvolution scheme first proposed by Kundur and Hatzinakos. Tests are reported on simulated and optical imaging problems. 1 Introduction A fundamental issue in image restoration is blur removal in the presence of observation noise. In the important case where the blurring operation is spatially invariant, then the basic restoration computation involved is simply a deconvolution process that faces the usual difficulties associated with ill-conditioning in the presence of noise [2]. The image observed from a shift invariant linear blurring process,...
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Subject Keyword	Rif Blind Image Deconvolution Deconvolution Process Blurring Operation Deconvolution Scheme Convolution Process Degradation Source Important Case Nonlinear Recursive Inverse Filter Partial Information True Image Shift Invariant Linear Blurring Process Usual Difficulty Observation Noise Basic Restoration Computation Blind Restoration Introduction Fundamental Issue Optical Imaging Problem Total Variation Regularization Degraded Image Imaging System Blur Removal Image Restoration
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