Image deconvolution using multigrid natural image prior and its applications

The natural image prior has been proven to be a powerful tool for image deblurring in recent years, though its performance against noise in various applications has not been thoroughly studied. In this paper, we present a multigrid natural image prior for image deconvolution that enhances its robust...

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Hauptverfasser:	Tingbo Hou, Sen Wang, Hong Qin, Miller, R L
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Deconvolution Image deblurring image denoising Image resolution Kernel natural image prior Noise reduction Pixel PSNR super-resolution
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creator	Tingbo Hou Sen Wang Hong Qin Miller, R L
description	The natural image prior has been proven to be a powerful tool for image deblurring in recent years, though its performance against noise in various applications has not been thoroughly studied. In this paper, we present a multigrid natural image prior for image deconvolution that enhances its robustness against noise, and afford three applications of image deconvolution using this prior: deblurring, super-resolution, and denoising. The prior is based on a remarkable property of natural images that derivatives with different resolutions are subject to the same heavy-tailed distribution with a spatial factor. It can serve in both blind and non-blind deconvolutions. The performances of the proposed prior in different applications are demonstrated by corresponding experimental results.
doi_str_mv	10.1109/ICIP.2010.5651083
format	Conference Proceeding
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subjects	Deconvolution Image deblurring image denoising Image resolution Kernel natural image prior Noise reduction Pixel PSNR super-resolution
title	Image deconvolution using multigrid natural image prior and its applications
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