Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 문영식 | - |
dc.date.accessioned | 2018-02-26T00:44:05Z | - |
dc.date.available | 2018-02-26T00:44:05Z | - |
dc.date.issued | 2015-10 | - |
dc.identifier.citation | JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, v. 81, No. 1, Page. 71-81 | en_US |
dc.identifier.issn | 1939-8018 | - |
dc.identifier.issn | 1939-8115 | - |
dc.identifier.uri | https://link.springer.com/article/10.1007/s11265-014-0903-2 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/40543 | - |
dc.description.abstract | This paper proposes a novel method that combines the discrete wavelet transform (DWT) and example-based technique to reconstruct a high-resolution from a low-resolution image. Although previous interpolation- and example-based methods consider the reconstruction adaptive to edge directions, they still have a problem with aliasing and blurring effects around edges. In order to address these problems, in this paper, we utilize the frequency sub-bands of the DWT that has the feature of lossless compression. Our proposed method first extracts the frequency sub-bands (Low-Low, Low-High, High-Low, High-High) from an input low-resolution image by the DWT, and then the low-resolution image is inserted into the Low-Low sub-band. Since information in high-frequency sub-bands (Low-High, High-Low, and High-High) might be lost in the low-resolution image, they are reconstructed or estimated by using example-based method from image patch database. After that, we make a high-resolution image by performing the inverse DWT of reconstructed frequency sub-bands. In experimental results, we can show that the proposed method outperforms previous approaches in terms of edge enhancement, reduced aliasing effects, and reduced blurring effects. © 2014, Springer Science+Business Media New York. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | SPRINGER | en_US |
dc.subject | Super-resolution | en_US |
dc.subject | Patch-based | en_US |
dc.subject | Discrete wavelet transform | en_US |
dc.subject | Local binary pattern | en_US |
dc.subject | LOCAL BINARY PATTERNS | en_US |
dc.subject | SUPER RESOLUTION | en_US |
dc.subject | TEXTURE CLASSIFICATION | en_US |
dc.subject | INTERPOLATION | en_US |
dc.title | Super-Resolution Image Reconstruction Using Wavelet Based Patch and Discrete Wavelet Transform | en_US |
dc.type | Article | en_US |
dc.relation.no | 1 | - |
dc.relation.volume | 81 | - |
dc.identifier.doi | 10.1007/s11265-014-0903-2 | - |
dc.relation.page | 71-81 | - |
dc.relation.journal | JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY | - |
dc.contributor.googleauthor | Shin, DK | - |
dc.contributor.googleauthor | Moon, YS | - |
dc.relation.code | 2015012441 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF COMPUTING[E] | - |
dc.sector.department | DIVISION OF COMPUTER SCIENCE | - |
dc.identifier.pid | ysmoon | - |
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