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A study on 2D signal noise reduction method for wavelet analysis

机译:小波分析的2D信号降噪方法研究

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A 2D signal is often used as an image signal in the application of a digital image, which could produce noise in the processing of image acquisition. It is too rough of a traditional method to be used for noise suppression; regarding noise suppression, it will also lose part of the original signal so that makes the image blurred. This paper introduces image reduction based on the wavelet analysis method, compares the effects of three methods: the inhibition of detail coefficients, the global threshold and distinction of the direction of threshold. We used Matlab software to simulate, and then choose the distinguishing different direction of threshold method to satisfy the requirements of the smoothness and similarity.
机译:在应用数字图像时通常用作图像信号,其可以在图像获取处理中产生噪声。它太粗糙了一种用于噪声抑制的传统方法;关于噪声抑制,它也将丢失原始信号的一部分,从而使图像模糊。本文介绍了基于小波分析方法的图像降低,比较了三种方法的效果:细节系数的抑制,全局阈值和阈值方向的区别。我们使用Matlab软件模拟,然后选择区别不同方向的阈值方法,以满足平滑度和相似性的要求。

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