多尺度域的分数阶微分图像增强  

Fractional Differential Enhancement in Multi-scale Domain

作　　者：袁赛杰 郭心悦[1] 王伟[2] YUAN Sai-jie;GUO Xin-yue;WANG Wei(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;The Naval Medicine Research Institute,Shanghai 200433,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093 [2]海军医学研究所,上海200433

出　　处：《软件导刊》2022年第12期153-161,共9页Software Guide

基　　金：国家自然科学基金项目(61501296);军内科研项目(HJ20172B02027)。

摘　　要：针对灰度图像增强过程中易发生细节丢失且易产生噪点的问题,提出一种基于拉普拉斯金字塔的RiemannLiouville分数阶微分图像增强算法。对传统Riemann-Liouville分数阶微分算子进行改进,使其适用于灰度图像,并将其像素值严格控制在0~255之间,以大幅减小失真,再引用拉普拉斯金字塔对原始图像进行分层增强,进一步提升图像的增强效果。鉴于该算法对细节有较强的保护作用,且对噪声有明显的抑制效果,故应用于医学超声图像中效果良好。实验结果表明,该算法提高了图像对比度,增强了图像边缘信息,且没有产生明显噪点,最大程度上保留了图像细节,在灰度图像尤其是超声图像领域有较好的应用前景。In process of gray image enhancement, details are always lost and unnecessary noise is easily generated,propose a Riemann-Liouville fractional differential image enhancement algorithm based on Laplacian pyramid. Firstly, the traditional Riemann-Liouville fractional differential operator is improved and its pixel value is strictly controlled between 0~255, which greatly reduces the distortion. Then, to further enhance the image enhancement, the Laplacian pyramid is applied to enhance the original image layer by layer. Given that its strong protection of details and obvious suppression of noise, the algorithm is also effective in medical ultrasound images. It can be observed from the experimental results that this method not only improves the contrast of the image and the edge information of the ultrasound image, but also highlights the target without producing obvious noise so that the image details to the greatest extent can be preserved. It has a great prospect in gray image especially in ultrasonic image field.

关 键 词：拉普拉斯金字塔 分数阶微分 灰度图像 超声图像 图像增强 抑制噪声 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]