Institute of Information Theory and Automation

Publication details

Multichannel blind iterative image restoration

Journal Article

Šroubek Filip, Flusser Jan


serial: IEEE Transactions on Image Processing vol.12, 9 (2003), p. 1094-1106

research: CEZ:AV0Z1075907

project(s): GA102/00/1711, GA ČR

keywords: conjugate gradient, half-quadratic regularization, multichannel blind deconvolution

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abstract (eng):

Very recently, an eigenvector-based method (EVAM) was proposed for a multichannel framework. We propose a novel iterative algorithm based on recent anisotropic denoising techniques of total variation and a Mumford-Shah functional with the EVAM restoration condition included. The algorithm performs well even on very noisy images and does not require an exact estimation of mask orders. We demonstrate capabilities of the algorithm on synthetic data, defocused images and on astronomical data.

Cosati: 09K

RIV: BD

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Last modification: 21.12.2012
Institute of Information Theory and Automation