基于多尺度曝光融合的医学CT图像增强方法  

Medical CT image enhancement method based on multi-scale exposure fusion

作　　者：史韶杰 韩建宁[1] 李大威 赵欣洒 马瑜涓 Shi Shaojie;Han Jianning;Li Dawei;Zhao Xinsa;Ma Yujuan(School of Information and Communication Engineering,North University of China,Taiyuan 030051,China)

机构地区：[1]中北大学信息与通信工程学院,太原030051

出　　处：《电子测量技术》2022年第6期106-111,共6页Electronic Measurement Technology

摘　　要：针对医学CT图像对比度和可见度较低导致不利于人眼观察及后期图像处理的问题,提出一种基于多尺度曝光融合框架的医学CT图像对比度增强算法,对医学CT图像实现增强。首先对原始图像进行拉普拉斯金字塔分解、重构,降低图像噪声对其的干扰,同时对图像细节增强。然后通过曝光合算法计算重构之后的图像的权重估计矩阵、曝光率以及图像的亮度转换函数,以此来对图像进行增强,使用该算法可以在图像对比度增强的同时,也提高了图像的可见度。实验表明,相比其他传统图像增强算法,该方法对图像的增强效果明显更优,对于医学CT图像的增强有着显著的增强效果。To address the problem that the low contrast and visibility of medical CT images are not conducive to human eye observation and post-processing, this paper proposes a contrast enhancement algorithm for medical CT images based on a multi-scale exposure fusion framework to achieve enhancement of medical CT images. Firstly, the original image is decomposed and reconstructed by Laplace pyramid to reduce the interference of image noise and enhance the image details. The image is then enhanced by calculating the weight estimation matrix, the exposure rate and the brightness conversion function of the reconstructed image using the exposure combination algorithm, which enhances the image contrast and improves the image visibility at the same time. Experiments show that the method is significantly better than other traditional image enhancement algorithms and has a significant enhancement effect on medical CT images.

关 键 词：CT图像 医学图像增强 曝光融合 拉普拉斯金字塔 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]