IEEE Trans Image Process - Patch-based near-optimal image denoising.

Tópicos

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Resumo

In this paper, we propose a denoising method motivated by our previous analysis of the performance bounds for image denoising. Insights from that study are used here to derive a high-performance practical denoising algorithm. We propose a patch-based Wiener filter that exploits patch redundancy for image denoising. Our framework uses both geometrically and photometrically similar patches to estimate the different filter parameters. We describe how these parameters can be accurately estimated directly from the input noisy image. Our denoising approach, designed for near-optimal performance (in the mean-squared error sense), has a sound statistical foundation that is analyzed in detail. The performance of our approach is experimentally verified on a variety of images and noise levels. The results presented here demonstrate that our proposed method is on par or exceeding the current state of the art, both visually and quantitatively.

Resumo Limpo

paper propos denois method motiv previous analysi perform bound imag denois insight studi use deriv highperform practic denois algorithm propos patchbas wiener filter exploit patch redund imag denois framework use geometr photometr similar patch estim differ filter paramet describ paramet can accur estim direct input noisi imag denois approach design nearoptim perform meansquar error sens sound statist foundat analyz detail perform approach experiment verifi varieti imag nois level result present demonstr propos method par exceed current state art visual quantit

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