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Efficient Recursive Multichannel Blind Image Restoration

Abstract

This paper presents a novel multichannel recursive filtering (MRF) technique to address blind image restoration. The primary motivation for developing the MRF algorithm to solve multichannel restoration is due to its fast convergence in joint blur identification and image restoration. The estimated image is recursively updated from its previous estimates using a regularization framework. The multichannel blurs are identified iteratively using conjugate gradient optimization. The proposed algorithm incorporates a forgetting factor to discard the old unreliable estimates, hence achieving better convergence performance. A key feature of the method is its computational simplicity and efficiency. This allows the method to be adopted readily in real-life applications. Experimental results show that it is effective in performing blind multichannel blind restoration.

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Correspondence to Li Chen.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Chen, L., Yap, K. & He, Y. Efficient Recursive Multichannel Blind Image Restoration. EURASIP J. Adv. Signal Process. 2007, 019675 (2006). https://doi.org/10.1155/2007/19675

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Keywords

  • Information Technology
  • Quantum Information
  • Conjugate Gradient
  • Primary Motivation
  • Fast Convergence