Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Comparative Study on Image Enhancement Methods for Low Contrast Images

저대비 영상을 위한 영상향상 기법들의 비교연구

  • 김용수 (대전대학교 컴퓨터공학부) ;
  • 김남진 (삼성전자 정보통신총괄 무선사업부) ;
  • 이세열 (청운대학교 컴퓨터학과)
  • Published : 2005.08.01
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Abstract

The principal objective of enhancement methods is to process an image so that the output image is more suitable than the original image lot a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compared the performance of Image Contrast Enhancement Technique Using Clustering Algorithm(ICECA) with those of color adjustment methods such as Histogram Equalization(HE), Brightness Preserving Bi-Histogram Equalization(BBHE), and the Multi-Scale Refiner(MSR). We compared these methods by applying the image enhancement methods to a set of diverse images.

영상 향상기법들의 주요한 목적은 특정한 응용프로그램에서 결과영상이 원영상보다 보다 적절하게 하기 위해 처리하는 것이다. 야간에 촬영한 영상들은 열약한 주위환경에 기인하여 저대비 영상을 가질 수 있다. 본 논문에서는 클러스터링 알고리듬을 이용한 영상 대비 향상 기법(ICECA)과 히스토그램 평활화(HE), 양분 히스토램 평활화(BBHE), Multi-Scale Retinek(MSR)와 같은 영상 향상 기법들을 비교하였다. 성능 비교를 위해 다양한 영상에 영상 향상기법들을 적용하여 비교하였다.

Keywords

References

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