首页> 外文会议>Proceedings of 2012 IEEE 3rd international conference on emergency management and management sciences >NSCT Remote Sensing Image Denoising Based on Threshold of Free Distributed FDR
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NSCT Remote Sensing Image Denoising Based on Threshold of Free Distributed FDR

机译:基于自由分布式FDR阈值的NSCT遥感图像降噪

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A new method for image denoising based on the free distributed hypothesis test threshold (FDR) and the non-sub-sampled contourlet transform (NSCT) is proposed in this paper. This method firstly acquires the free distributed false discovery rate hypotheses test in statistics to set the threshold in the NSCT domain, and then removes the noise through soft threshold function, which doesn't depend on the length of signal. The experimental results show that the proposed method can more effectively reduce Gaussian noise and improve the peak value signalto-noise ratio in the remote sensing image; Meanwhile, this method utilizes the shift invariant of NSCT transform to inhibit the pseudo Gibbs distortion effect, and integrally preserves the texture and edge etc..details' information of the image, thus obviously ameliorate the visual effect of the image.
机译:提出了一种基于自由分布假设检验阈值(FDR)和非子采样轮廓波变换(NSCT)的图像去噪新方法。该方法首先在统计中获取自由分布的错误发现率假设检验,以在NSCT域中设置阈值,然后通过软阈值函数消除噪声,该函数不依赖于信号长度。实验结果表明,该方法可以更有效地降低高斯噪声,提高遥感图像中的峰值信噪比。同时,该方法利用NSCT变换的位移不变性来抑制伪吉布斯失真效应,并整体保留图像的纹理和边缘等细节信息,从而明显改善了图像的视觉效果。

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