基于小波-Contourlet的Bayes估计医用红外热图去噪方法  

Medical Infrared Image Denoising Based on Bayes Adaptive Estimates of Wavelet-contourlet Transform

作　　者：张国栋[1] 张泾周[1] 杨蕊[1] 李辉[1] 

机构地区：[1]西北工业大学自动化学院,西安710072

出　　处：《科学技术与工程》2012年第26期6652-6656,共5页Science Technology and Engineering

摘　　要：医用红外图像去噪已经成为医学图像实际应用中不可或缺的一项工作。为了获得更好的去噪效果,提出了一种基于小波-Contourlet(WBCT)变换的Bayes自适应估计医用红外热图去噪方法。并且,与图像循环平移算法(Cycle Spinning)相结合,提高信噪比,更好地体现图像的边缘和纹理等特征信息。在Matlab环境下进行仿真研究。结果表明,这种算法能够获得更高的信噪比,使视觉效果得到明显的改善。Medical infrared image denoising has become an integral part of the practical application of medical image. In order to get a better denoising, medical infrared image denoising based on Byes adaptive estimates of Wavelet-Contourlet transfcrrm is proposed, which combines with Cycle Spinning to improve signal to noise ratio, to rightly reflect the image edge and texture feature information. In the Matlab environment, the simulation results show that this algorithm can achieve a higher signal to noise ratio and better visual effects.

关 键 词：医用热图去噪 小波-CONTOURLET变换 自适应估计 循环平移 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]