High Density Impulse Noise Removal Based on the Total Observation Kernel Element for Image Sequences

• Item type: Journal(1)
• 公開日: 2014-08-15
• タイトル: High Density Impulse Noise Removal Based on the Total Observation Kernel Element for Image Sequences
• タイトル / 言語: en
• タイトル: High Density Impulse Noise Removal Based on the Total Observation Kernel Element for Image Sequences
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [一般論文] impulse noise removal, image sequences, frames, PSNR, MSSIM
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University／Information Technology and Computer Science Program, Brawijaya University
• 著者所属: Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University
• 著者所属: Priority Organization for Innovation and Excellence, Kumamoto University
• 著者所属(英): en
• 著者所属(英): Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University / Information Technology and Computer Science Program, Brawijaya University
• 著者所属(英): en
• 著者所属(英): Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University
• 著者所属(英): en
• 著者所属(英): Priority Organization for Innovation and Excellence, Kumamoto University
• 著者名: Fitri, Utaminingrum; Keiichi, Uchimura; Gou, Koutaki
• 著者名(英): Fitri, Utaminingrum; Keiichi, Uchimura; Gou, Koutaki
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Several different methods for impulse noise removal in image sequences have been proposed. However, all of them are not successful in removing high density of impulse noise. Hence, this paper proposes a filtering method for reducing high density impulse noise in the image sequences. We use three windows with size 3 × 3 to obtain a new window with similar size. Three windows are taken from the next-frame, current frames and previous frames. The recursive window is applied in the current frames. The filtering process uses decision-based method. Meanwhile, a pixel for replacing the noisy pixel is calculated from a new window based on weighting method. Our experimental results show that the proposed method can not only reduce the high impulse noise in image sequences well, but also preserve more details and textures.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.22(2014) No.4 (online); DOI http://dx.doi.org/10.2197/ipsjjip.22.679; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Several different methods for impulse noise removal in image sequences have been proposed. However, all of them are not successful in removing high density of impulse noise. Hence, this paper proposes a filtering method for reducing high density impulse noise in the image sequences. We use three windows with size 3 × 3 to obtain a new window with similar size. Three windows are taken from the next-frame, current frames and previous frames. The recursive window is applied in the current frames. The filtering process uses decision-based method. Meanwhile, a pixel for replacing the noisy pixel is calculated from a new window based on weighting method. Our experimental results show that the proposed method can not only reduce the high impulse noise in image sequences well, but also preserve more details and textures.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.22(2014) No.4 (online); DOI http://dx.doi.org/10.2197/ipsjjip.22.679; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 55, 号 8, 発行日 2014-08-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764