计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220300265-7.doi: 10.11896/jsjkx.220300265

• 图像处理&多媒体技术 • 上一篇    下一篇

基于亮度校正和融合通道先验的内窥镜图像增强算法

安子恒, 徐超, 冯博, 韩俱宝   

  1. 安徽大学集成电路学院 合肥 230601
  • 出版日期:2023-06-10 发布日期:2023-06-12
  • 通讯作者: 徐超(graymagpie@163.com)
  • 作者简介:(838928122@qq.com)
  • 基金资助:
    国家重点研发计划(2019YFC0117800)

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).

摘要: 为了解决医学内窥镜图像中存在的光照不均匀、黏膜下组织血管模糊、对比度低等问题,文中提出了一种新颖的内窥镜图像增强算法。该方法分为两部分,第一部分采用象限剪裁直方图伽马校正的方法实现亮度增强,首先对亮度通道的直方图进行分象限剪裁得到平滑的累积分布函数(CDF),然后利用截断CDF的方式来控制伽马参数的大小;第二部分基于融合通道先验增强图像的对比度和清晰度,首先利用离散小波变换融合图像的绿色通道和红色通道,得到细节丰富的图层,用于生成图像形成模型(IFM)的初始透射图,然后通过提出的理想函数模型校正初始透射图,得到清晰的图像,最后结合CLAHE实现组织和血管的对比度增强。在实验室自建的MEDS数据集上,将所提方法和其他几种现有方法进行主观和客观分析,结果表明所提方法在提高血管和组织对比度的同时,避免了图像过度增强。

关键词: 亮度, 伽马校正, 对比度, 透射图, 离散小波变换, 内窥镜

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

中图分类号: 

  • TP391
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