四川大学学报（自然科学版）2018，Vol.55Issue(2)：316-322,7.DOI:10.3969/j.issn.0490-6756.2018.02.017
基于灰度DAG熵最大化量化分辨率医学图像增强
Gray level DAG maximum entropy based on quantization resolution for medical image tone enhancement
摘要
Abstract
In order to improve the medical image sharpness and contrast,and improve the computational efficien-cy,the authors proposed the gray level DAG maximum entropy based on quantization resolution for Medical im-age tone enhancement.Firstly,the authors used a simple piecewise autoregressive(Piecewise Autoregressive PAR)image target model for recovery,and taked into account the error of analog to digital conversion to use least squares algorithm to estimate PAR model parameter,which obtain high resolution image histogram resto-ration model;Secondly,aiming at the problem of low contrast may exist,the least squares algorithm for con-strained optimization problems was modeled in DAG,which constructed a hue preserving constraint optimization model of maximum entropy image enhancement,and the characteristics of the DAG figure Monge theorem was used to reduce the computational complexity;Through the above two steps,the image details and contrast en-hancement in the process of medical image enhancement are realized.The simulation results show that the pro-posed algorithm can provide more effective medical image enhancement effect.关键词
图像增强/有向无环图/分段自回归/最小二乘/色调保持/最大熵Key words
Image enhancement/Directed acyclic graph/Piecewise autoregressive/Least squares/Color retention/Maximum entropy分类
信息技术与安全科学引用本文复制引用
宋璐,冯艳平,卫亚博..基于灰度DAG熵最大化量化分辨率医学图像增强[J].四川大学学报（自然科学版）,2018,55(2):316-322,7.基金项目
中医药行业科研专项(201207002) （201207002）
