Multichannel Image Blind Deconvolution for Noisy Measurements

Joao Alvim, Kenji Nose Filho, Renato R Lopes

DOI: 10.14209/sbrt.2023.1570915716

Evento: XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023)

Keywords: Multichannel Blind Deconvolution Inverse Problems Non-linear Optimization SIMO systems

Abstract

This paper focuses in the analysis of Multichannel Blind Deconvolution (MBD) techniques over noiseless and noisy data. We use both REgularization by Denoising (RED) and the multichannel blind criterion as a new approach to regularize the ill posed inverse problem of image deblurring. Tests with different optimization techniques, such as fixed step, global search and the Barzilai-Browein (BB) step direction were performed in synthetic data and the results were compared to other techniques in the literature.

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