...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Image Processing On Line >Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors
【24h】

Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors

机译：基于张量高阶奇异值分解的去噪算法的实现

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This article presents an implementation of a denoising algorithm based on High-Order Singular Value Decomposition (HOSVD) of tensors. It belongs to the class of patch-based methods such as BM3D and NL-Bayes. It exploits the grouping of similar patches in a local neighbourhood into a 3D matrix also called a third order tensor. Instead of performing different processing in different dimension, as in BM3D for instance, it is based on the decomposition of a tensor simultaneously in all dimensions reducing it to a core tensor in a similar way as SVD does for matrices in computing the diagonal matrix of singular values. The core tensor is filtered and a tensor is reconstructed by inverting the HOSVD. As common in patch-based algorithms, all tensors containing a pixel are then merged to produce an output image.
机译：本文提出了一种基于张量的高阶奇异值分解（HOSVD）的去噪算法的实现。它属于基于补丁的方法类别，例如BM3D和NL-Bayes。它利用将局部邻域中的相似面片分组到3D矩阵（也称为三阶张量）中。而不是像在BM3D中那样在不同维度上执行不同的处理，它基于同时在所有维度上分解张量，以类似于SVD对矩阵计算奇异对角矩阵的方式将其缩减为核心张量。价值观。对核心张量进行滤波，并通过反转HOSVD重建张量。与基于补丁的算法一样，然后将包含像素的所有张量合并以生成输出图像。

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