Medical Image Denoising Using Mixed Transforms

J. S. Jameel
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引用次数: 2

Abstract

In this paper, a mixed transform method is proposed based on a combination of wavelet transform (WT) and multiwavelet transform (MWT) in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI) or Computed Tomography (CT) images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results show that a high peak signal to noise ratio (PSNR) is improved significantly and the characteristic features are well preserved by employing mixed transform of WT and MWT due to their capability of separating noise signals from image signals. Moreover, the corresponding mean square error (MSE) is decreased accordingly compared to other available methods.
基于混合变换的医学图像去噪
提出了一种基于小波变换和多小波变换相结合的混合变换方法对医学图像进行去噪。为了提高图像处理的去噪性能,该方法采用小波变换和最大波变换的级联形式。实际上,第一步是在磁共振成像(MRI)或计算机断层扫描(CT)图像中添加噪声以进行测试。对噪声图像进行小波变换处理,得到4个子带,每个子带分别进行小波变换处理,然后进行软/硬去噪。仿真结果表明,利用小波变换和小波变换的混合变换可以有效地分离噪声信号和图像信号,大大提高了图像的峰值信噪比,并保留了图像的特征。与其他方法相比,相应的均方误差(MSE)也相应减小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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