RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      KCI등재

      중요 화소들을 이용한 광원의 색 추정 방법

      한글로보기

      https://www.riss.kr/link?id=A99680509

      • 0

        상세조회
      • 0

        다운로드
      서지정보 열기
      • 내보내기
      • 내책장담기
      • 공유하기
      • 오류접수

      부가정보

      다국어 초록 (Multilingual Abstract)

      It is a challenging problem to most of the image processing when the light source is unknown. The color of the light source must be estimated in order to compensate color changes. To estimate the color of the light source, additional assumption is need, so that we assumed color distribution according to the light source. If the pixels, which do not satisfy the assumption, are used, the estimation fails to provide an accurate result. The most popular color distribution assumption is Grey-World Assumption (GWA); it is the assumption that the color in each scene, the surface reflectance averages to gray or achromatic color over the entire images. In this paper, we analyze the characteristics of the camera response function, and the effect of the Grey-World Assumption on the pixel value and chromaticity, based on the inherent characteristics of the light source. Besides, we propose a novel method that detects important pixels for the color estimation of the light source. In our method, we firstly proposed a method that gives weights to pixels satisfying the assumption. Then, we proposed a pixel detection method, which we modified max-RGB method, to apply on the weighted pixels. Maximum weighted pixels in the column direction and row direction in one channel are detected. The performance of our method is verified through demonstrations in several real scenes. Proposed method better accurately estimate the color of the light than previous methods.
      번역하기

      It is a challenging problem to most of the image processing when the light source is unknown. The color of the light source must be estimated in order to compensate color changes. To estimate the color of the light source, additional assumption is nee...

      It is a challenging problem to most of the image processing when the light source is unknown. The color of the light source must be estimated in order to compensate color changes. To estimate the color of the light source, additional assumption is need, so that we assumed color distribution according to the light source. If the pixels, which do not satisfy the assumption, are used, the estimation fails to provide an accurate result. The most popular color distribution assumption is Grey-World Assumption (GWA); it is the assumption that the color in each scene, the surface reflectance averages to gray or achromatic color over the entire images. In this paper, we analyze the characteristics of the camera response function, and the effect of the Grey-World Assumption on the pixel value and chromaticity, based on the inherent characteristics of the light source. Besides, we propose a novel method that detects important pixels for the color estimation of the light source. In our method, we firstly proposed a method that gives weights to pixels satisfying the assumption. Then, we proposed a pixel detection method, which we modified max-RGB method, to apply on the weighted pixels. Maximum weighted pixels in the column direction and row direction in one channel are detected. The performance of our method is verified through demonstrations in several real scenes. Proposed method better accurately estimate the color of the light than previous methods.

      더보기

      참고문헌 (Reference)

      1 길종인, "컬러 및 깊이 데이터 변환을 이용하는 입체감 향상" 한국방송공학회 16 (16): 584-595, 2011

      2 이재원, "최대 색차신호 표를 이용한 Retinex 영상의 컬러 향상" 한국방송공학회 17 (17): 851-863, 2012

      3 조동찬, "색채 항상성 방법과 경계 영역 기반 히스토그램 평활화 방법을 이용한 영상의 화질 향상 방법" 한국방송공학회 15 (15): 332-345, 2010

      4 M.D. Grossberg, "What is the Space of Camera Response Functions?" 2003

      5 E. Land, "Lightness and retinex theory" 61 : 1-11, 1971

      6 B. Phong, "Illumination for computer generated pictures" 18 : 311-317, 1975

      7 R.T. Tan, "Illumination Chromaticity Estimation using Inverse-Intensity Chromaticity Space" 673-682, 2003

      8 A. Gijsenij, "Generalized gamut mapping using image derivative structures for color constancy" 86 (86): 127-139, 2010

      9 J. van de Weijer, "Edge-based color constancy" 16 (16): 2207-2214, 2007

      10 A. Gijsenij, "Color Constancy using Natural Image Statistics and Scene Semantics" 33 (33): 687-698, 2011

      1 길종인, "컬러 및 깊이 데이터 변환을 이용하는 입체감 향상" 한국방송공학회 16 (16): 584-595, 2011

      2 이재원, "최대 색차신호 표를 이용한 Retinex 영상의 컬러 향상" 한국방송공학회 17 (17): 851-863, 2012

      3 조동찬, "색채 항상성 방법과 경계 영역 기반 히스토그램 평활화 방법을 이용한 영상의 화질 향상 방법" 한국방송공학회 15 (15): 332-345, 2010

      4 M.D. Grossberg, "What is the Space of Camera Response Functions?" 2003

      5 E. Land, "Lightness and retinex theory" 61 : 1-11, 1971

      6 B. Phong, "Illumination for computer generated pictures" 18 : 311-317, 1975

      7 R.T. Tan, "Illumination Chromaticity Estimation using Inverse-Intensity Chromaticity Space" 673-682, 2003

      8 A. Gijsenij, "Generalized gamut mapping using image derivative structures for color constancy" 86 (86): 127-139, 2010

      9 J. van de Weijer, "Edge-based color constancy" 16 (16): 2207-2214, 2007

      10 A. Gijsenij, "Color Constancy using Natural Image Statistics and Scene Semantics" 33 (33): 687-698, 2011

      11 G. Buchsbaum, "A spatial processor model for object colour perception" 310 (310): 1-26, 1980

      12 D. Forsyth, "A novel algorithm for color constancy" 5 (5): 5-36, 1990

      13 F. Ciurea, "A large image database for color constancy research" 2003

      더보기

      동일학술지(권/호) 다른 논문

      동일학술지 더보기

      더보기

      분석정보

      View

      상세정보조회

      0

      Usage

      원문다운로드

      0

      대출신청

      0

      복사신청

      0

      EDDS신청

      0

      동일 주제 내 활용도 TOP

      더보기

      주제

      연도별 연구동향

      연도별 활용동향

      연관논문

      연구자 네트워크맵

      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

      인용정보 인용지수 설명보기

      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2017-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2016-01-15 학회명변경 한글명 : 한국방송공학회 -> 한국방송∙미디어공학회
      영문명 : The Korean Society Of Broadcast Engineers -> The Korean Institute of Broadcast and Media Engineers
      KCI등재
      2013-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2006-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2004-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
      더보기

      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.38 0.38 0.34
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.32 0.27 0.526 0.14
      더보기

      이 자료와 함께 이용한 RISS 자료

      나만을 위한 추천자료

      해외이동버튼