Automatic Colorization of Near-Infrared Monochrome Face Image based on Position-Dependent Regression

• Item type: SIG Technical Reports(1)
• 公開日: 2013-05-23
• タイトル: Automatic Colorization of Near-Infrared Monochrome Face Image based on Position-Dependent Regression
• タイトル / 言語: en
• タイトル: Automatic Colorization of Near-Infrared Monochrome Face Image based on Position-Dependent Regression
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 卒論ショートアピール
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Wakayama University
• 著者所属: Wakayama University
• 著者所属: Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者名: Atsushi, Mori; Toshikazu, Wada; Hiroshi, Oike
• 著者名(英): Atsushi, Mori; Toshikazu, Wada; Hiroshi, Oike
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This report presents a method for estimating color face images from near-infrared monochrome face images. This estimation is done by the regression from a monochrome image to a color image. One difficult problem is that the regression depends on face organs. That is, the same intensity pixels in an infrared monochrome image do not correspond to the same color pixels. Therefore, entirely uniform regression cannot colorize the pixels correctly. This report presents a colorization method for monochrome face images by position-dependent regressions, where the regression coefficients are obtained in different image regions corresponding to facial organs. Also, we can extend the independent variables by adding texture information around the pixels so as to obtain accurate color images. However, unrestricted extension may cause multi-collinearity problem, which may produce inaccurate results. This report also proposes CCA based dimensionality reduction for avoiding this problem. Comparative experiments on the restoration accuracy demonstrate the superiority of our method.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This report presents a method for estimating color face images from near-infrared monochrome face images. This estimation is done by the regression from a monochrome image to a color image. One difficult problem is that the regression depends on face organs. That is, the same intensity pixels in an infrared monochrome image do not correspond to the same color pixels. Therefore, entirely uniform regression cannot colorize the pixels correctly. This report presents a colorization method for monochrome face images by position-dependent regressions, where the regression coefficients are obtained in different image regions corresponding to facial organs. Also, we can extend the independent variables by adding texture information around the pixels so as to obtain accurate color images. However, unrestricted extension may cause multi-collinearity problem, which may produce inaccurate results. This report also proposes CCA based dimensionality reduction for avoiding this problem. Comparative experiments on the restoration accuracy demonstrate the superiority of our method.
• 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: AA11131797
• 書誌情報: 研究報告コンピュータビジョンとイメージメディア（CVIM）; 巻 2013-CVIM-187, 号 34, p. 1-6, 発行日 2013-05-23
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会