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영상의 명암대비 향상을 위한 차별적 압축 방법 기반의 히스토그램 평활화

Histogram Equalization based on Differential Compression for Image Contrast Enhancement

  • 이재원 (전남대학교 전자컴퓨터공학과) ;
  • 홍성훈 (전남대학교 전자컴퓨터공학부, 정보통신연구소)
  • Lee, Jae-Won (Dept. of Electronic and Computer Engineering, Chonnam National University) ;
  • Hong, Sung-Hoon (School of Electronic and Computer Engineering, Chonnam National Univ. & Information and Telecommunication Research Institute)
  • 투고 : 2013.11.19
  • 심사 : 2014.01.13
  • 발행 : 2014.01.30

초록

기존 히스토그램 평활화 방법을 사용하여 영상의 명암대비를 증가시킬 경우 과도한 밝기 변화로 인한 과포화 현상(over-enhancement), 계조현상(false contouring) 및 영상의 세부 정보가 없어지는 등의 왜곡이 발생한다. 특히 밝기 분포가 특정한 밝기 레벨에 밀집되어 있는 경우 이러한 왜곡이 두드러지게 나타나게 된다. 이러한 문제를 해결하기 위하여 임계치를 이용한 히스토그램 클리핑을 통해 입력 히스토그램을 변형하는 개선된 평활화 방법들이 제시되었지만, 입력영상의 히스토그램 특성을 고려하지 않고 전체 히스토그램에 대해 동일한 임계치를 적용하기 때문에 명암대비 향상효과가 감소하고, 입력 영상의 특성을 유지하지 못해 부자연스러운 영상이 얻어지기도 한다. 본 논문에서는 기존 방식에서 발생하는 문제를 해결하기 위하여 입력영상의 히스토그램의 빈도수에 따른 차별적 압축방법을 적용하여 과도한 밝기 변화가 발생하는 문제를 억제하면서도 입력영상의 특성을 유지하는 새로운 평활화 방식을 제 안한다. 또한 입력영상의 특성에 따라 압축률의 강도를 제어하여 보다 효과적으로 명암대비 향상을 수행하는 방법을 제시한다.

In case of contrast of the image enhancement by using the conventional histogram equalization, over-enhancement, false contouring and distortion such as the details disappearance of the image occurs due to the excessive brightness change. Especially, these distortion appears when the brightness distribution is concentrated in a particular brightness level. In order to solve these problems, improved histogram equalization methods to transform the input histogram by clipping using threshold have been proposed, but contrast enhancement effect is reduced because it does not consider the characteristics of the input image's histogram to apply the same threshold for the entire histogram, and unnatural image is obtained because it does not retain the characteristics of the image. In this paper, to solve the problems of existing methods, we propose new equalization method that suppress excessive brightness changes by applying to the differential compression according to the histogram frequency, and maintain the characteristics of the input image. In addition, we propose a more effectively method to improve contrast by controlling the strength of the compression ratio depending on the characteristics of the input image.

키워드

참고문헌

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