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Randomly valued impulse noise removal using Gaussian curvature of image surface

机译:使用高斯图像表面的高斯曲率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。它通过计算所有像素的高斯曲率来检测图像表面上的尖锐尖峰或陡峭的山谷,并通过使用电视修正来消除它们。通常,曲率趋于在峰和谷的阳性和极大的值。我们可以利用此属性,并使用它来准确地通过迭代地施加次数来准确地检测脉冲噪声。数值实验结果表明,该方法在噪声检测和恢复的图像质量方面优于传统方法,特别是在随机值脉冲的情况下。

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