Automatic denoising of 2D color face images using recursive PCA reconstruction
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Hyun | - |
dc.contributor.author | Moon, Young Shik | - |
dc.date.accessioned | 2021-06-23T21:37:03Z | - |
dc.date.available | 2021-06-23T21:37:03Z | - |
dc.date.created | 2021-02-01 | - |
dc.date.issued | 2006-09 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/44694 | - |
dc.description.abstract | In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise components on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following six steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model and alignment of the input face to mean shape, reconstruction of an initial noise free face, relighting of reconstructed face using a bilateral filter, extraction of noise regions using the variances of skin color of training data, and reconstruction using partial information of input images. (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denoising method maintains the structural characteristics of input faces, while efficiently removing noise components with complex colors. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.title | Automatic denoising of 2D color face images using recursive PCA reconstruction | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Moon, Young Shik | - |
dc.identifier.doi | 10.1007/11864349_73 | - |
dc.identifier.scopusid | 2-s2.0-33750274563 | - |
dc.identifier.wosid | 000241489100073 | - |
dc.identifier.bibliographicCitation | ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS, v.4179, pp.799 - 809 | - |
dc.relation.isPartOf | ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS | - |
dc.citation.title | ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS | - |
dc.citation.volume | 4179 | - |
dc.citation.startPage | 799 | - |
dc.citation.endPage | 809 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalClass | 3 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.subject.keywordPlus | ENHANCEMENT | - |
dc.subject.keywordAuthor | Impulse Noise | - |
dc.subject.keywordAuthor | Bilateral Filter | - |
dc.subject.keywordAuthor | Denoising Method | - |
dc.subject.keywordAuthor | Reconstructed Face | - |
dc.subject.keywordAuthor | Input Face | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/11864349_73 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
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.