首页> 外文会议>International Symposium on Visual Computing;ISVC 2008 >Robust Estimation Approach for NL-Means Filter
【24h】

Robust Estimation Approach for NL-Means Filter

机译:NL-均值滤波器的鲁棒估计方法

获取原文

摘要

Edge preserved smoothing techniques have gained importance for the purpose of image denoising. A good edge preserving filter is given by NL-means filter than any other linear model based approaches. Since the weight function in NL-means filter is closely related to the error norm and influence function in robust estimation framework, this paper explores a refined approach of NL-means filter by using robust estimation function rather than the usual exponential function for its weight calculation. Here the filter output at each pixel is the weighted average of pixels in the surrounding neighborhoods using the chosen robust M-estimator function. Validations using various test images have been analyzed and the results were compared with the other known recent methods. There is a reason to believe that this refined algorithm has some interesting and notable points.
机译:边缘保留的平滑技术对于图像去噪的目的已经变得越来越重要。与任何其他基于线性模型的方法相比,NL-均值滤波器提供了一个很好的边缘保留滤波器。由于NL-均值滤波器的权重函数与鲁棒估计框架中的误差范数和影响函数密切相关,因此本文通过使用鲁棒估计函数而不是通常的指数函数来探索NL-均值滤波器的改进方法。 。在这里,每个像素的滤波器输出是使用选定的鲁棒M估计函数在周围邻域中像素的加权平均值。分析了使用各种测试图像的验证,并将结果与​​其他已知的最新方法进行了比较。有理由相信,这种改进的算法具有一些有趣且值得注意的要点。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号