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HOSAKA TADAAKI
Department Undergraduate School , School of Science and Technology Position Associate Professor |
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| Language | English |
| Publication Date | 2011/02 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Image Quality Enhancement for Single-Image Super Resolution Based on Local Similarities and Support Vector Regression |
| Contribution Type | Co-authored (other than first author) |
| Journal | IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES |
| Journal Type | Another Country |
| Publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG |
| Volume, Issue, Page | E94A(2),pp.552-554 |
| Author and coauthor | Atsushi Yaguchi,Tadaaki Hosaka,Takayuki Hamamoto |
| Details | In reconstruction-based super resolution, a high-resolution image is estimated using multiple low-resolution images with sub-pixel misalignments. Therefore, when only one low-resolution image is available, it is generally difficult to obtain a favorable image. This letter proposes a method for overcoming this difficulty for single- image super resolution. In our method, after interpolating pixel values at sub-pixel locations on a patch-by-patch basis by support vector regression, in which learning samples are collected within the given image based on local similarities, we solve the regularized reconstruction problem with a sufficient number of constraints. Evaluation experiments were performed for artificial and natural images, and the obtained high-resolution images indicate the high-frequency components favorably along with improved PSNRs. |
| DOI | 10.1587/transfun.E94.A.552 |
| ISSN | 0916-8508/1745-1337 |