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。
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.
出处
《中国图象图形学报》
CSCD
北大核心
2011年第1期21-26,共6页
Journal of Image and Graphics
基金
国家自然科学基金项目(60872109)
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
pulse coupled neural networks
image factorization
medical image enhancement
human visual properties
