基于pde的正则化方法与统一框架的比较

2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control Pub Date : 2014-09-18 DOI:10.1109/IMCCC.2014.114

Bochao Su, Xiaohua Zhang, Wanyu Liu, Li Li

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引用次数: 0

摘要

计算机视觉中常见的问题包括去噪、伪影消除和结构保留或增强。基于偏微分方程的非线性扩散滤波器可能是实现这些目标的一种可能性。本文对三种典型的基于pde的正则化算法进行了比较，并提出了一个通用框架，这对分析基于pde的正则化方法具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparison of the PDE-Based Regularization Methods and a Unifying Framework

The frequent problems in computer vision consist of de-noising, artifact elimination as well as structure preserving or enhancing. PDE-based nonlinear diffusion filter may be one possibility to achieve those goals. In this paper, we perform comparison of three typical PDE-based regularization algorithms followed by the proposal of a general framework, which exploits fundamental significance for analyzing PDE-based regularization methods.

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2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control

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