Name
Abstract | ||
|---|---|---|
Image denoising algorithms often assume an additive white Gaussian noise (AWGN) process that is independent of the actual RGB values. Such approaches are not fully automatic and cannot effectively remove color noise produced by todays 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 noise level function 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 algorithm, which is shown to outperform state-of-the-art denoising algorithms. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TPAMI.2007.1176 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
automatic estimation,underlying clean image,piecewise smooth image model,real noise level function,noise level,color noise,image brightness,single image,per-segment image variance,noise level function,additive white gaussian noise,computer vision,awgn,image segmentation,standard deviation,vision system,conditional random field,gaussian noise,upper bound,colored noise,brightness,random processes,noise reduction | Value noise,Computer vision,Colors of noise,Median filter,Pattern recognition,Computer science,Non-local means,Image noise,Artificial intelligence,Image restoration,Gaussian noise,Color image | Journal |
Volume | Issue | ISSN |
30 | 2 | 0162-8828 |
Citations | PageRank | References |
191 | 6.84 | 42 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ce Liu | 1 | 3347 | 188.04 |
| Richard Szeliski | 2 | 21300 | 2104.74 |
| Sing Bing Kang | 3 | 5064 | 345.13 |
| C. Lawrence Zitnick | 4 | 7321 | 332.72 |
| William T. Freeman | 5 | 17382 | 1968.76 |