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Hokkaido University Collection of Scholarly and Academic Papers >
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Missing Intensity Interpolation Using a Kernel PCA-Based POCS Algorithm and its Applications
| Title: | Missing Intensity Interpolation Using a Kernel PCA-Based POCS Algorithm and its Applications |
| Authors: | Ogawa, Takahiro Browse this author →KAKEN DB | | Haseyama, Miki Browse this author →KAKEN DB |
| Keywords: | Image enlargement | | interpolation | | kernel principal component analysis (PCA) | | missing area restoration | | projection onto convex sets (POCS) |
| Issue Date: | Feb-2011 |
| Publisher: | IEEE - Institute of Electrical and Electronics Engineers |
| Journal Title: | IEEE Transactions on Image Processing |
| Volume: | 20 |
| Issue: | 2 |
| Start Page: | 417 |
| End Page: | 432 |
| Publisher DOI: | 10.1109/TIP.2010.2070072 |
| PMID: | 20801740 |
| Abstract: | A missing intensity interpolation method using a kernel PCA-based projection onto convex sets (POCS) algorithm and its applications are presented in this paper. In order to interpolate missing intensities within a target image, the proposed method reconstructs local textures containing the missing pixels by using the POCS algorithm. In this reconstruction process, a nonlinear eigenspace is constructed from each kind of texture, and the optimal subspace for the target local texture is introduced into the constraint of the POCS algorithm. In the proposed method, the optimal subspace can be selected by monitoring errors converged in the reconstruction process. This approach provides a solution to the problem in conventional methods of not being able to effectively perform adaptive reconstruction of the target textures due to missing intensities, and successful interpolation of the missing intensities by the proposed method can be realized. Furthermore, since our method can restore any images including arbitrary-shaped missing areas, its potential in two image reconstruction tasks, image enlargement and missing area restoration, is also shown in this paper. |
| Rights: | © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/44871 |
| 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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