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基于PCNN图像因子分解的X线医学图像增强
引用本文:何胜宗,刘映杰,马义德,宋文强,邓海波.基于PCNN图像因子分解的X线医学图像增强[J].中国图象图形学报,2011,16(1):21-26.
作者姓名:何胜宗  刘映杰  马义德  宋文强  邓海波
作者单位:兰州大学信息科学与工程学院,兰州大学信息科学与工程学院,兰州大学信息科学与工程学院,兰州大学信息科学与工程学院,兰州大学信息科学与工程学院
基金项目:国家自然科学基金项目(60872109)
摘    要:提出一种基于人眼视觉特性和改进的PCNN图像因子分解的X线医学图像增强算法。利用一种改进的PCNN图像因子分解算法对图像进行因子分解,得到细节程度由粗糙到精细的 一系列图像因子。分别对各层图像因子平滑滤波获得图像因子增益矩阵,根据图像因子的局部对比度是否达到由人眼视觉特性得到的对比度阈值进行自适应调节增益矩阵,对每层 图像因子增强后重构即可得到增强图像。经过对不同X线医学图像进行实验仿真,并对比一些常用图像增强算法,取得了较好的增强效果。

关 键 词:脉冲耦合神经网络    图像因子分解    医学图像增强    人眼视觉特性
收稿时间:6/15/2009 4:32:49 PM
修稿时间:2010/9/22 0:00:00

Medical X-ray image enhancement based on PCNN image factorization
He Shengzong,Liu Yingjie,Ma Yide,Song Wenqiang and Deng Hai bo.Medical X-ray image enhancement based on PCNN image factorization[J].Journal of Image and Graphics,2011,16(1):21-26.
Authors:He Shengzong  Liu Yingjie  Ma Yide  Song Wenqiang and Deng Hai bo
Affiliation:Lanzhou University,School of information science and engineering,,School of information science and engineering, Lanzhou University,,
Abstract:An algorithm for medical X-ray image enhancement based on human visual properties and improved PCNN image factorization is proposed. Using the improved image factorization algorithm, an image is decomposed into a set of image factors which are ordered from coarse to fine in details. Each factor is separately smoothed to obtain a gain matrix and then the matrix is adjusted adaptively according to whether its local contrast reaches the contrast threshold resulting from human visual properties. The enhanced image is reconstructed from the enhanced factors. Through simulations to different medical X-ray images, a better effect is achieved compared with common image enhancement methods.
Keywords:pulse coupled neural networks  image factorization  medical image enhancement  human visual properties
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