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Randomly valued impulse noise removal using Gaussian curvature of image surface

机译:使用图像表面高斯曲率的随机值脉冲噪声去除

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A novel impulse noise removal using Gaussian curvature is proposed. It detects sharp-pointed peaks or steep valleys on the image surface by calculating Gaussian curvatures at all pixels and removes them by using TV inpainting. Generally, the curvature tends to take positive and extremely large values at peaks and valleys. We can take advantage of this property and use it to accurately detect impulse noise by applying several thresholds iteratively in decreasing order. Results of numerical experiments showed that the proposed method is superior to conventional methods in terms of both noise detection and restored image quality, especially in case of randomly valued impulse.
机译:提出了一种使用高斯曲率的新型脉冲噪声去除方法。它通过计算所有像素处的高斯曲率来检测图像表面上的尖峰或陡谷,并使用电视修复技术将其去除。通常,曲率倾向于在峰和谷处取正值和非常大的值。我们可以利用此属性,并以递减的顺序迭代应用几个阈值,从而将其用于准确检测脉冲噪声。数值实验结果表明,该方法在噪声检测和恢复图像质量方面均优于传统方法,尤其是在随机值脉冲的情况下。

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