基于x -let的医学图像去噪

L. Parthiban, R. Subramanian
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引用次数: 16

摘要

小波被证明可以很好地适应一维信号,但由于其定向选择性差,只能捕获有限的二维方向信息。曲线变换和轮廓变换具有非常高的方向特异性,这是医学图像所必需的。这些变换基于一定的各向异性标度原理,与小波的各向同性标度有很大不同。对超声图像、磁共振图像和计算机断层扫描图像等医学图像进行了仿真试验,结果表明,在均方误差、信噪比和视觉评价方面,曲线波和轮廓波去噪效果优于小波去噪
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Denoising using X-lets
Wavelets are proved to be well adapted for 1-D signal but can only capture limited directional information in 2D due to its poor orientation selectivity. Transforms like curvelets and contourlets have very high degree of directional specificity which is necessary for medical images. These transforms are based on certain anisotropic scaling principle which is quite different from the isotropic scaling of wavelets. Simulation test carried out on medical images like ultrasound images, magnetic resonance images and computerized tomography scan images, show that better denoising results were obtained by curvelets and contourlets, than with wavelets, in terms of mean square error, signal to noise ratio and visual evaluation
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