首页> 外文会议>Control and Decision Conference (CCDC), 2012 24th Chinese >Study on the image de-noising algorithm of adaptive threshold based on wavelet transform in the unclear radiation environment
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Study on the image de-noising algorithm of adaptive threshold based on wavelet transform in the unclear radiation environment

机译:辐射不清晰环境下基于小波变换的自适应阈值图像去噪算法研究

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In order to get a better image in the nuclear radiation environment, this paper presents an adaptive threshold image de-nosing algorithm based on the concept of wavelet multi-resolution. First of all, remove the big isolated points by median filtering in the image; achieve the multi-resolution analysis by lifting wavelet transform; then obtain the threshold value of the wavelet coefficients by the Bayesian Shrink adaptive algorithm; finally recover the image by the inverse lifting wavelet transform. As a result of multi-resolution adaptive threshold method, the non-stationary characteristics of the signal can be described quite well, and remove the noise according to the distribution of the signal and noise at different resolutions. The experimental results show that this method can get a better de-nosing effect in the nuclear radiation environment.
机译:为了在核辐射环境中获得更好的图像,本文提出了一种基于小波多分辨率概念的自适应阈值图像去噪算法。首先,通过图像中值滤波去除较大的孤立点;通过提升小波变换实现多分辨率分析;然后通过贝叶斯收缩自适应算法获得小波系数的阈值。最终通过逆提升小波变换恢复图像。作为多分辨率自适应阈值方法的结果,可以很好地描述信号的非平稳特性,并根据信号的分布和不同分辨率的噪声消除噪声。实验结果表明,该方法在核辐射环境中可以获得较好的降噪效果。

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