Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Medical Image Enhancement Using an Adaptive Nonlinear Histogram Stretching

적응적 비선형 히스트그램 스트레칭을 이용한 의료영상의 화질향상

  • Kim, Seung-Jong (Department of Computer Information, Hanyang Women's University)
  • 김승종 (한양여자대학교 컴퓨터정보과)
  • Received : 2014.09.17
  • Accepted : 2015.01.08
  • Published : 2015.01.31
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Abstract

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Finally, an adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.

의료영상에서 잡음을 제거하는 것과 명암대비를 좋게하는 것은 화질을 향상시키는 중요한 방법이다. 본 논문에서는 의료영상의 화질 향상을 위해 에지 기반 잡음 제거 방법과 적응적 비선형 히스토그램 스트레칭 알고리즘을 제안한다. 첫째, 웨이블릿 변환을 수행하고 분해된 고주파 부밴드 각각에 대해 Haar 변환을 수행한다. 동시에 수평, 수직, 대각 방향의 Sobel 마스크를 적용하여 방향별 에지를 검출한다. 둘째, 고주파 부밴드에 대해 에지 기반 적응적 문턱치를 이용하여 잡음을 제거한다. 셋째, 적응적 가중치를 이용하여 고주파 부밴드 계수 값을 향상한 후, Haar 역변환 및 웨이블릿 역변환을 수행하여 복원영상을 얻는다. 마지막으로 복원된 영상의 화소 값의 범위가 좁아졌으므로 제안하는 비선형 히스토그램 스트레칭 알고리즘을 이용하여 명암대비가 향상된 영상을 얻는다. 제안한 알고리즘을 낮은 명암대비를 갖는 의료영상에 적용했을 경우 효율적으로 에지를 보존하면서도 시각적으로 우수한 결과를 얻었다.

Keywords

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