Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220300265-7.doi: 10.11896/jsjkx.220300265

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Endoscopic Image Enhancement Algorithm Based on Luminance Correction and Fusion Channel Prior

AN Ziheng, XU Chao, FENG Bo, HAN Jubao   

  1. School of Integrated Circuits,Anhui University,Hefei 230601,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:AN Ziheng,born in 1999,postgraduate.His main research interests include image processing and deep learning. XU Chao,born in 1962,Ph.D,professor.His main research interests include network intelligent information system and image processing.
  • Supported by:
    National Key Research and Development Program of China(2019YFC0117800).

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Abstract: In order to solve the problems of uneven illumination,blurred blood vessels in submucosal tissue,and low contrast in medical endoscopic images,a novel endoscopic image enhancement algorithm is proposed in this paper.The method is divided into two parts.The first part uses a method based on quadrant clipping histogram gamma correction to achieve brightness enhancement.In this part,the histogram of the brightness channel is first divided into quadrant clipping to obtain a smooth cumulative distribution function(CDF),and then use the truncated CDF way to control the size of the gamma parameter.The second part enhances the contrast and sharpness of the image based on the fusion channel prior.This part first uses discrete wavelet transform to fuse the green channel and red channel of the image to obtain a layer with rich details,which is used to generate the initial transmission map of the Image Formation Model(IFM).After that,the initial transmission image is corrected by the proposed ideal function model,and a clear image is obtained.finally,the contrast enhancement of tissue and blood vessels is realized by combining with CLAHE.The method and several other existing methods are analyzed subjectively and objectively on the MEDS dataset built by the laboratory.The results show that the proposed method can improve the contrast of blood vessels and tissues while avoiding excessive image enhancement.

Key words: Luminance, Gamma correction, Contrast, Transmission map, Discrete wavelet transform, Endoscope

CLC Number: 

  • TP391
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