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Image inpainting based on energy minimization
http://hdl.handle.net/10061/11321
http://hdl.handle.net/10061/1132195e02cd8-3cf3-40a8-bb57-04f081918ed9
名前 / ファイル | ライセンス | アクション |
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2016-12-26 | |||||
タイトル | ||||||
タイトル | Image inpainting based on energy minimization | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | image inpainting | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | image completion | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | energy minimization | |||||
資源タイプ | ||||||
資源タイプ | conference paper | |||||
アクセス権 | ||||||
アクセス権 | open access | |||||
著者 |
Kawai, Norihiko
× Kawai, Norihiko× Sato, Tomokazu× Yokoya, Naokazu |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Image inpainting techniques have been widely used to remove undesired visual objects in images such as damaged portions of photographs and people who have accidentally entered into pictures. Conventionally, the missing parts of an image are completed by optimizing the objective function which is defined based on the sum of SSD (sum of squared differences). However, the naive SSD-based objective function is not robust against intensity change in an image. Thus, unnatural intensity change often appears in the missing parts. In addition, when an image has continuously changing texture patterns, the completed texture in a resultant image sometimes blurs due to inappropriate pattern matching. In this paper, in order to improve the image quality of the completed texture, the conventional objective function is newly extended by considering intensity changes and spatial locality to prevent unnatural intensity changes and blurs in a resultant image. By minimizing the extended energy function, the missing regions can be completed without unnatural intensity changes and blurs. In experiments, the effectiveness of the proposed method is successfully demonstrated by applying our method to various images and comparing the results with those obtained by the conventional method. | |||||
書誌情報 |
巻 6498, 発行日 2007 |
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会議情報 | ||||||
会議名 | Computational Imaging V | |||||
開催期間 | Jan 28, 2007 | |||||
開催地 | San Jose CA | |||||
開催国 | USA | |||||
出版者 | ||||||
出版者 | SPIE | |||||
出版者版DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1117/12.702976 | |||||
権利 | ||||||
権利情報 | Copyright c 2007 SPIE | |||||
著者版フラグ | ||||||
出版タイプ | AM |