Multichannel blind iterative image restoration

0411117 - UTIA-B 20030104 RIV US eng J - Journal Article
Šroubek, Filip - Flusser, Jan
Multichannel blind iterative image restoration.
IEEE Transactions on Image Processing. Roč. 12, č. 9 (2003), s. 1094-1106. ISSN 1057-7149. E-ISSN 1941-0042
R&D Projects: GA ČR GA102/00/1711
Institutional research plan: CEZ:AV0Z1075907
Keywords : conjugate gradient * half-quadratic regularization * multichannel blind deconvolution
Subject RIV: BD - Theory of Information
Impact factor: 2.642, year: 2003
http://library.utia.cas.cz/prace/20030104.pdf

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.
Permanent Link: http://hdl.handle.net/11104/0131204