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Gradients-Predict Filter of Multiple-Scale Template

机译:多尺度模板的梯度预测过滤器

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Noise filtering is an essential part of any image processor, whether the final image is utilized for visual interpretation or for automatic analysis. Arithmetic Mean Filter (AMF) and Standard Median Filter (SM) tend to work well for fixed-valued impulses but poorly for random-valued impulse noise. The authors review the current trend of image filter development. Some papers present new ways to identify corrupted pixels,while others strongly emphasize on suppressing the noise ratio. And some summarized the both and combined to present new complicated scheme. As widely known, Vector Median Filter (VMF) has the disadvantage of replacing too many uncorrupted image pixels. New method form R. H. Chan, Chung-Wa Ho, and M. Nikolova in 2005 is capable of restoring images corrupted by salt-and-pepper noise with extremely high noise ratio, but the calculation is so complex that it is only can be treated as a post-processing image enhancement procedure. In the fact, the modern imaging equipment is good enough and will not produce more than three percent of salt-and-pepper noise. But as a pretreatment of Image Analysis,filter should focus on preservation the original details and simple or fast for the engineering. Our purpose in this paper is to present a simple scheme to preserve uncorrupted, original pixels, but still enables to remove corrupted ones with a good balance the algorithm complexity and the efficiency.
机译:无论最终图像用于视觉解释还是自动分析,噪声过滤都是任何图像处理器的重要组成部分。算术均值滤波器(AMF)和标准中值滤波器(SM)往往对于固定值的脉冲效果很好,但对于随机值的脉冲噪声效果较差。作者回顾了图像过滤器发展的当前趋势。一些论文提出了识别损坏像素的新方法,而另一些论文则着重强调抑制噪声比。有人总结了两者并结合起来提出了新的复杂方案。众所周知,向量中值滤波器(VMF)具有替换过多未损坏图像像素的缺点。 2005年的RH Chan,Chung-Wa Ho和M.Nikolova的新方法能够以极高的噪声比恢复盐和胡椒噪声损坏的图像,但是计算非常复杂,只能将其视为后处理图像增强过程。实际上,现代的成像设备已经足够好,不会产生超过百分之三的盐和胡椒粉噪声。但是作为图像分析的预处理,过滤器应着重于保留原始细节,并为工程提供简单或快速的支持。我们在本文中的目的是提出一种简单的方案来保留未损坏的原始像素,但仍然能够在算法复杂度和效率之间取得良好的平衡,以去除损坏的像素。

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