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Salt-and-pepper noise removal by adaptive median-based lifting filter using second-generation wavelets - Springer

机译:使用第二代小波通过自适应中值提升滤波器去除椒盐噪声-Springer

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摘要

In this paper, we propose a novel adaptive median-based lifting filter for image de-noising which has been corrupted by homogeneous salt and pepper noise. The median-based lifting filter removes the noise of the input image by calculating the median of the neighboring significant pixels. The algorithm for image noise removal uses the lifting scheme of the second-generation wavelets in conjunction with the proposed adaptive median-based lifting filter. The experimental results demonstrate the efficiency of the proposed method. The proposed algorithm is compared with all the basic filters, and it is found that our method outperforms many other algorithms and it can remove salt and pepper noise with a noise level as high as 90%. The algorithm works exceedingly well for all levels of noise, as illustrated in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) measures.
机译:在本文中,我们提出了一种新颖的基于中值的自适应提升滤波器,用于图像去噪,该滤波器已被均一的盐和胡椒噪声破坏。基于中位数的提升滤波器通过计算相邻有效像素的中位数来消除输入图像的噪声。图像噪声去除算法结合了第二代小波的提升方案和提出的自适应基于中值的提升滤波器。实验结果证明了该方法的有效性。将提出的算法与所有基本滤波器进行比较,发现我们的方法优于许多其他算法,并且可以去除高达90%噪声的盐和胡椒噪声。如峰值信噪比(PSNR)和结构相似性指数(SSIM)度量所示,该算法对所有级别的噪声都非常有效。

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