Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Contrast Enhancement Using a Density based Sub-histogram Equalization Technique

밀도기반의 분할된 히스토그램 평활화를 통한 대비 향상 기법

  • Yoon, Hyun-Sup (Department of Electrical Engineering, Soongsil University) ;
  • Han, Young-Joon (Department of Electrical Engineering, Soongsil University) ;
  • Hahn, Hern-Soo (Department of Electrical Engineering, Soongsil University)
  • Published : 2009.01.25
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Abstract

In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes those regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrast in the images and the results are compared to the conventional approaches to show its superiority.

영상에서 밝기의 분포가 밀집된 영역에 포함되는 특징은 구분이 어렵다. 이러한 문제의 해결을 위해 전역 혹은 지역 명암대비 향상기법을 사용하게 되며 주로 히스토그램의 평활화 기법이 적용된다. 기존의 전역 명암대비 향상기법을 적용하는 경우 밝기 밀집 정도를 고려하지 않아서 지나치게 밝거나 너무 어두운 값으로 변환하는 문제를 만들고, 지역 명암대비 향상기법은 결과 영상에서 특징을 분리해버리거나 밝기분포의 불규칙성으로 인해 부자연스러운 영상을 만들어내는 결과를 보여주기도 한다. 본 논문은 이러한 문제를 해결하기 위해 히스토그램을 밀집정도를 기준으로 분할하고, 각 분할된 히스토그램의 평활화 범위를 분할영역의 평균과 분산을 고려하여 결정하는 방법을 제안한다. 제안하는 방법은 평활화를 밀집영역의 밝기범위와 밀집정도를 고려하여 평활화하는 최고 및 최저 밝기를 결정함으로써 지나친 밝기의 변화를 최소화하고, 밀도가 낮은 나머지 영역들에 대해 분리된 평활화를 수행함에 따라 이들 영역의 특징들이 사라지지 않고 향상시키는 효과를 거둘 수 있다. 히스토그램의 분할 및 평활화 범위를 결정하는 방법도 본 논문에서 제시되었다. 제안된 방법의 성능의 우수성은 다양한 밝기 영역을 갖는 실험영상들을 대상으로 기존의 방법들과 비교실험을 통해 입증하였다.

Keywords

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