两种Perona-Malik模型去噪参数选择的研究

A. Nasonov, N. Mamaev, A. Krylov
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引用次数: 0

摘要

本文采用两种模型解决了Perona-Malik图像扩散算法去噪时无参考参数的选择问题。该方法的思想是分析噪声输入图像与输入图像中存在结构化数据的去噪算法的结果之间的差异。分析包括互信息的计算——一个显示结构化数据和噪声之间比率的值。我们将该方法应用于摄影图像、矢量图形图像以及具有不同参数高斯噪声的视网膜图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Investigation of Denoising Parameters Choice in two Perona-Malik Models
The paper addresses the problem of no-reference parameter choice for image denoising by Perona-Malik image diffusion algorithm using two models. The idea of the approach is to analyze the difference image between noisy input image and the outcome of the denoising algorithm for the presence of structured data from the input image. The analysis consists of the calculation of the mutual information — a value that shows the ratio between the structured data and the noise. We apply the proposed method to photographic images, vector graphics images and to retinal images with modeled Gaussian noise with different parameters.
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