| Presentation | 2021-12-03 Optimizing Block Size for Low-Level Gaussian Noise Estimation Takashi Suzuki, Hiroyuki Tsuji, Tomoaki Kimura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The estimation method based on MAD (Median Absolute Deviation) exists as a method for estimating the standard deviation σ of Gaussian noise in the image. This estimation method divides the image into 16×16 blocks and calculates the standard deviation for each block. Then, the standard deviation of the Gaussian noise superimposed on the image is estimated using the blocks that are considered to be flat areas and the block size is a fixed size of 16×16. However, in the image with many edges and detailed signals, the fixed size of 16×16 may reduce the number of blocks that are considered as flat areas. As a result, the accuracy of the standard deviation of the estimated Gaussian noise will be reduced. In this paper, we investigate the optimal block size for low-level Gaussian noise depending on the amount of edge and detail signals in the image. The proposed method divides the image into several block sizes and estimates the standard deviation of Gaussian noise by MAD-based noise estimation method for each of them. The standard deviation of the Gaussian noise is then estimated by applying the coefficients from the fuzzy set, controlled by the edge and detail signal content of the image, to the standard deviation for each block size. In this result, the error can be reduced by 5.3% in the low-level Gaussian noise image compared with the conventional method using MAD. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Gaussian Noise / Noise Estimation / Standard Deviation / MAD |
| Paper # | SIS2021-28 |
| Date of Issue | 2021-11-26 (SIS) |
| Conference Information | |
| Committee | SIS |
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| Conference Date | 2021/12/3(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Noriaki Suetake(Yamaguchi Univ.) |
| Vice Chair | Tomoaki Kimura(Kanagawa Inst. of Tech.) / Naoto Sasaoka(Tottori Univ.) |
| Secretary | Tomoaki Kimura(NTT) / Naoto Sasaoka(National Inst. of Tech., Ube College) |
| Assistant | Soh Yoshida(Kansai Univ.) / Yoshiaki Makabe(Kanagawa Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Smart Info-Media Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Optimizing Block Size for Low-Level Gaussian Noise Estimation |
| Sub Title (in English) | |
| Keyword(1) | Gaussian Noise |
| Keyword(2) | Noise Estimation |
| Keyword(3) | Standard Deviation |
| Keyword(4) | MAD |
| 1st Author's Name | Takashi Suzuki |
| 1st Author's Affiliation | Micro-Technica Co., Ltd.(Micro-Technica) |
| 2nd Author's Name | Hiroyuki Tsuji |
| 2nd Author's Affiliation | Kanagawa Institute of Technology(KAIT) |
| 3rd Author's Name | Tomoaki Kimura |
| 3rd Author's Affiliation | Kanagawa Institute of Technology(KAIT) |
| Date | 2021-12-03 |
| Paper # | SIS2021-28 |
| Volume (vol) | vol.121 |
| Number (no) | SIS-284 |
| Page | pp.pp.37-42(SIS), |
| #Pages | 6 |
| Date of Issue | 2021-11-26 (SIS) |