Remote sensing image enhancement based on singular value decomposition
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ha, Changwoo | - |
dc.contributor.author | Kim, Wonkyun | - |
dc.contributor.author | Jeong, Jechang | - |
dc.date.accessioned | 2022-07-16T08:48:27Z | - |
dc.date.available | 2022-07-16T08:48:27Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2013-08 | - |
dc.identifier.issn | 0091-3286 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162262 | - |
dc.description.abstract | A satellite image enhancement method based on singular value decomposition (SVD) is presented. The proposed method consists mainly of four steps: image decomposition, adjustable contrast enhancement, noise reduction, and image composition. The method decomposes an image into its singular values, from which the luminance information can be obtained using SVD. In turn, adjustable contrast enhancement is applied by changing the singular values, which are controlled by characteristic-based contrast-level parameters. In the noise reduction process, the high-frequency elements, such as noise, are removed using rank approximation. In the final image composition process, the proposed algorithm combines color and luminance components in order to preserve color consistency. Experimental results show that the proposed scheme has less noise than the conventional methods and improves contrast performance while preserving details. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS | - |
dc.title | Remote sensing image enhancement based on singular value decomposition | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeong, Jechang | - |
dc.identifier.doi | 10.1117/1.OE.52.8.083101 | - |
dc.identifier.scopusid | 2-s2.0-84907900691 | - |
dc.identifier.wosid | 000324290900012 | - |
dc.identifier.bibliographicCitation | OPTICAL ENGINEERING, v.52, no.8 | - |
dc.relation.isPartOf | OPTICAL ENGINEERING | - |
dc.citation.title | OPTICAL ENGINEERING | - |
dc.citation.volume | 52 | - |
dc.citation.number | 8 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Optics | - |
dc.relation.journalWebOfScienceCategory | Optics | - |
dc.subject.keywordPlus | CONTRAST ENHANCEMENT | - |
dc.subject.keywordPlus | HISTOGRAM EQUALIZATION | - |
dc.subject.keywordAuthor | remote sensing image enhancement | - |
dc.subject.keywordAuthor | contrast enhancement | - |
dc.subject.keywordAuthor | noise reduction | - |
dc.subject.keywordAuthor | singular value decomposition | - |
dc.identifier.url | https://www.spiedigitallibrary.org/journals/optical-engineering/volume-52/issue-8/083101/Remote-sensing-image-enhancement-based-on-singular-value-decomposition/10.1117/1.OE.52.8.083101.short | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.