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Image Denoising Algorithm Based on Edge-Preserving Self-Snake Model and Wavelet-Based PDE

机译:基于边缘保留自蛇模型和基于小波的PDE的图像去噪算法

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In this paper, a so-called edge-preserving self-snake model (EPSSM) that is able to remove noise while preserving edge features will be built, and using wavelet and partial differential equation (PDE), an integrated algorithm of wavelet-based PDE (IAWP) of image denoising is proposed. In integrated algorithm, The EPSSM is firstly used to remove noise of an input image, then we decompose the processed image by wavelet transform and its three high frequency coefficients are filtered by the EPSSM, finally, denoised image is reconstructed using inverse wavelet transform. The denoising performance of two proposed algorithms is measured according to PSNR values, and the experiments show that our methods have a better performance than others.
机译:在本文中,将建立能够消除噪声的所谓的边缘保留自蛇模型(EPSSM),并使用小波和部分微分方程(PDE),基于小波的集成算法提出了图像去噪的PDE(IAWP)。在集成算法中,首先使用EPSSM来消除输入图像的噪声,然后我们通过小波变换分解处理的图像,并且其三个高频系数被EPSSM滤波,最后,使用逆小波变换重建去噪图像。根据PSNR值测量两个提出算法的去噪性能,实验表明,我们的方法具有比其他方法更好的性能。

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