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A Comparative Performance Analysis of Discrete Wavelet Transforms for Denoising of Medical Images

机译:医学图像去噪的离散小波变换的比较绩效分析

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摘要

In general, during image acquisition and transmission, digital images are corrupted by noises due to various effect. The complex type of additive noises disturbs images, depending on the storage and capture devices. These medical imaging devices are not noise free. The medical images used for diagnosis are acquired from Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray Instruments. Reduction of visual quality due to addition of noise complicates the treatment and diagnosis. Removal of additive noise in images can easily be possible using simple threshold methods. In this paper we proposed an algorithm for denoising using Discrete Wavelet Transform (DWT). Numerical results shows the performance (based on parameters like: PSNR, MSE, MAE) of algorithm using various wavelet transforms for different Medical Images corrupted by random noise.
机译:通常,在图像采集和传输期间,由于各种效果,数字图像被噪声损坏。复杂类型的添加剂噪声扰乱图像,取决于存储和捕获设备。这些医学成像装置不是无噪音。用于诊断的医学图像从磁共振成像(MRI),计算机断层扫描(CT)和X射线仪器中获取。由于添加噪声而降低视觉质量使治疗和诊断具有复杂化。使用简单的阈值方法可以容易地去除图像中的添加剂噪声。在本文中,我们提出了一种使用离散小波变换(DWT)去噪的算法。数值结果显示了使用各种小波变换的算法的性能(基于以下参数:PSNR,MSE,MAE),用于随机噪声损坏的不同医学图像。

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