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2008

Automatic Estimation and Removal of Noise from a Single Image

10 years 2 months ago
Automatic Estimation and Removal of Noise from a Single Image
Image denoising algorithms often assume an additive white Gaussian noise (AWGN) process that is independent of the actual RGB values. Such approaches cannot effectively remove color noise produced by today's CCD digital camera. In this paper, we propose a unified framework for two tasks: automatic estimation and removal of color noise from a single image using piecewise smooth image models. We introduce the noise level function (NLF), which is a continuous function describing the noise level as a function of image brightness. We then estimate an upper bound of the real NLF by fitting a lower envelope to the standard deviations of per-segment image variances. For denoising, the chrominance of color noise is significantly removed by projecting pixel values onto a line fit to the RGB values in each segment. Then, a Gaussian conditional random field (GCRF) is constructed to obtain the underlying clean image from the noisy input. Extensive experiments are conducted to test the proposed...
Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawre
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where PAMI
Authors Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawrence Zitnick, William T. Freeman
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