Technical Program

Paper Detail

Paper IDD-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
TimeThursday, 10 December, 15:30 - 17:15
Presentation Time:Thursday, 10 December, 16:45 - 17:00 Check your Time Zone
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.