Paper ID | D-3-2.6 |
Paper Title |
Rapid and Accurate Local Gaussian Noise Removal |
Authors |
shogo seta, Yusuke Nakahara, Takuro Yamaguchi, Masaaki ikehara, Keio University, Japan |
Session |
D-3-2: Multimedia Analysis and Others |
Time | Thursday, 10 December, 15:30 - 17:15 |
Presentation Time: | Thursday, 10 December, 16:45 - 17:00 Check your Time Zone |
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All times are in New Zealand Time (UTC +13) |
Topic |
Image, Video, and Multimedia (IVM): |
Abstract |
In this paper, we propose a rapid and high-accuracy Gaussian noise removal method by applying the learning linear filter used in RAISR for super-resolution. Our algorithm is a rapid local method, yet produces comparable results to the accuracy of the non-local method known for its high accuracy. The novelty of this paper is that the same processing as super-resolution is incorporated into denoising. The conventional local processing includes smoothing processing, and has a problem that high-frequency components of an original signal are lost while reducing the noise. In order to solve the problem, this method incorporates a super-resolution method that compensates for high-frequency components as post-processing. The super-resolution method utilizes a process that applies a learning linear filter according to the feature of patches in RAISR. Because the proposed method consists of local precessing, its operation is rapid compared to non local processing like BM3D. |