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Wiener-Based Inpainting Quality Prediction
Title: | Wiener-Based Inpainting Quality Prediction |
Authors: | OGAWA, Takahiro Browse this author →KAKEN DB | TANAKA, Akira Browse this author | HASEYAMA, Miki Browse this author →KAKEN DB |
Keywords: | quality prediction | inpainting | Wiener filter | least-squares estimation |
Issue Date: | 1-Oct-2017 |
Publisher: | Institute of Electronics, Information and Communication Engineers |
Journal Title: | IEICE Transactions on Information and Systems |
Volume: | E100.D |
Issue: | 10 |
Start Page: | 2614 |
End Page: | 2626 |
Publisher DOI: | 10.1587/transinf.2017EDP7058 |
Abstract: | A Wiener-based inpainting quality prediction method is presented in this paper. The proposed method is the first method that can predict inpainting quality both before and after the intensities have become missing even if their inpainting methods are unknown. Thus, when the target image does not include any missing areas, the proposed method estimates the importance of intensities for all pixels, and then we can know which areas should not be removed. Interestingly, since this measure can be also derived in the same manner for its corrupted image already including missing areas, the expected difficulty in reconstruction of these missing pixels is predicted, i.e., we can know which missing areas can be successfully reconstructed. The proposed method focuses on expected errors derived from the Wiener filter, which enables least-squares reconstruction, to predict the inpainting quality. The greatest advantage of the proposed method is that the same inpainting quality prediction scheme can be used in the above two different situations, and their results have common trends. Experimental results show that the inpainting quality predicted by the proposed method can be successfully used as a universal quality measure. |
Rights: | Copyright ©2017 The Institute of Electronics, Information and Communication Engineers |
Relation: | https://search.ieice.org/ |
Type: | article |
URI: | http://hdl.handle.net/2115/67806 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 小川 貴弘
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