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Image Denoising Based on Dilated Singularity Prior

机译:基于膨胀奇异先验的图像去噪

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摘要

In order to preserve singularities in denoising, we propose a new schemeby adding dilated singularity prior to noisy images. The singularities are detected bycanny operator firstly and then dilated using mathematical morphology for findingpixels “near” singularities instead of “on” singularities. The denoising results for pixelsnear singularities are obtained by nonlocal means in spatial domain to preserve singularitieswhile the denoising results for pixels in smooth regions are obtained by EMalgorithm constrained by a mask formed by downsampled spatial image with dilatedsingularity prior to suiting the sizes of the subbands of wavelets. The final denoised resultsare got by combining the above two results. Experimental results show that the schemecan preserve singularity well with relatively high PSNR and good visual quality.
机译:为了在去噪中保持奇异性,我们提出了一种通过在噪声图像之前添加膨胀奇异性的新方案。先由奇异运算符检测奇异点,然后使用数学形态学对其进行扩张,以查找“近”奇点而不是“上”奇点的像素。在空间域中通过非局部手段获得像素附近的奇异点的去噪结果,以保留奇异性,而在平滑小区域内像素的去噪结果通过EM算法算法获得,该算法受具有降奇异性的降采样空间图像形成的掩模的EM算法约束,然后再适合小波子带的大小。 。最终的去噪结果是通过结合以上两个结果而得到的。实验结果表明,该方案能够以较高的PSNR和良好的视觉质量很好地保持奇异性。

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