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Missing Image Data Reconstruction Based on Adaptive Inverse Projection via Sparse Representation

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Title: Missing Image Data Reconstruction Based on Adaptive Inverse Projection via Sparse Representation
Authors: Ogawa, Takahiro Browse this author →KAKEN DB
Haseyama, Miki Browse this author
Keywords: Image reconstruction
image texture analysis
interpolation
inverse projection
sparse representation
Issue Date: Oct-2011
Publisher: IEEE
Journal Title: IEEE Transactions on Multimedia
Volume: 13
Issue: 5
Start Page: 974
End Page: 992
Publisher DOI: 10.1109/TMM.2011.2161760
Abstract: In this paper, a missing image data reconstruction method based on an adaptive inverse projection via sparse representation is proposed. The proposed method utilizes sparse representation for obtaining low-dimensional subspaces that approximate target textures including missing areas. Then, by using the obtained low-dimensional subspaces, inverse projection for reconstructing missing areas can be derived to solve the problem of not being able to directly estimate missing intensities. Furthermore, in this approach, the proposed method monitors errors caused by the derived inverse projection, and the low-dimensional subspaces optimal for target textures are adaptively selected. Therefore, we can apply adaptive inverse projection via sparse representation to target missing textures, i.e., their adaptive reconstruction becomes feasible. The proposed method also introduces some schemes for color processing into the calculation of subspaces on the basis of sparse representation and attempts to avoid spurious color caused in the reconstruction results. Consequently, successful reconstruction of missing areas by the proposed method can be expected. Experimental results show impressive improvement of our reconstruction method over previously reported reconstruction methods.
Rights: © 2011 IEEE. Reprinted, with permission, from Ogawa, T, Haseyama, M., Missing Image Data Reconstruction Based on Adaptive Inverse Projection via Sparse Representation, IEEE Transactions on Multimedia, Oct. 2011. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Hokkaido University products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Type: article (author version)
URI: http://hdl.handle.net/2115/47216
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)

Submitter: 小川 貴弘

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