Robust, blind multichannel image identification and restoration using stack decoder. Issue 3 (30th January 2019)

• Record Type: Journal Article
• Authors: Boudjenouia, Fouad; Abed‐Meraim, Karim; Chetouani, Aladine; Jennane, Rachid
• Is Part Of: IET image processing. Volume 13:Issue 3(2019)
• Page Start: 475
• Page End: 482
• Publication Date: 2019-01-30
• Subjects: blind equalisers -- deconvolution -- channel estimation -- identification -- image restoration; stack decoder -- solutions -- improvements -- multichannel blind image deconvolution problem -- authors -- simplified version -- existing cross‐relation method -- blind system identification -- channel estimation cost function -- channel identification -- image restoration method -- stack decoding algorithm -- improved mixed norm regularisation -- image restoration tasks -- channel order estimation -- blind multichannel image identification; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.5243
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : In this study, the authors introduce new solutions and improvements to the multi‐channel blind image deconvolution problem. More precisely, authors' contributions are threefold: (i) At first, a simplified version of the existing cross‐relation method for blind system identification is proposed; but most importantly, the authors incorporate into the channel estimation cost function a sparsity constraint to deal with the challenging issue of channel order overestimation errors; (ii) then, once the channel identification is achieved, a new image restoration method based on the stack decoding algorithm is introduced; and (iii) finally, a refining approach using an 'all‐at‐once' optimisation technique with an improved mixed norm regularisation is considered. The performance of the proposed approach was evaluated using several numerical simulations. Blind system identification and image restoration tasks were evaluated with respect to several criteria: numerical complexity, robustness to noise effects and channel order estimation. The results obtained are promising and highlight the effectiveness of the proposed approach.