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首页> 外文期刊>Journal of Medical Imaging and Health Informatics >Enhancement of Medical Images Based on Guided Filter in Nonsubsampled Shearlet Transform Domain
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Enhancement of Medical Images Based on Guided Filter in Nonsubsampled Shearlet Transform Domain

机译:基于引导滤波器在非求沉岩变换域的引导滤光片的增强

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摘要

In order to deal with the pseudo-Gibbs phenomenon and noise interference in image processing, a medical image enhancement approach based on the nonsubsampled shearlet transform (NSST) theory is proposed in this paper. The whole process of the method can be divided into the followingsteps: First, the original image is decomposed into one low-frequency sub-band and some high-frequency sub-bands; Second, the guided filter is used to adjust the low-frequency sub-band coefficients to enhance the contrast of the image, and the adaptive threshold is utilized to remove the noiseof the high-frequency sub-bands coefficients; Third, the processed coefficients are reconstructed with the inverse nonsubsampled shearlet transform, and the enhanced image is obtained. Extensive simulation results demonstrate the effectiveness of the proposed algorithm on enhancing the medicalimages compared to the state-of-the-art approaches.
机译:为了处理图像处理的伪GIBB现象和噪声干扰,本文提出了一种基于非法掌握的剪柏变换(NSST)理论的医学图像增强方法。 该方法的整个过程可以被分成下面的步骤:首先,原始图像被分解成一个低频子带和一些高频子带; 其次,引导滤波器用于调整低频子带系数以增强图像的对比度,并且使用自适应阈值来消除高频子带系数的噪声; 第三,用逆非管制的Shearlet变换重建处理的系数,获得增强图像。 广泛的仿真结果表明,与最先进的方法相比,提出了提高医学模仿的算法。

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