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图像扩散滤波的局部解析格式

Locally Analytic Schemes for Diffusion Filtering of Images
课程网址: http://videolectures.net/acs07_welk_las/  
主讲教师: Martin Welk
开课单位: 萨尔兰大学
开课时间: 2007-12-17
课程语种: 英语
中文简介:
非线性扩散滤波技术作为一种具有广泛应用前景的图像去噪方法,已得到广泛的应用。这类方法中最有趣的是张量驱动的各向异性扩散和奇异各向同性扩散滤波器,如总变分流。由于不同的原因,为这些滤波器设计好的数值算法是具有挑战性的。空间离散化将非线性扩散偏微分方程转化为常微分方程组。他们的研究使人们对基于扩散的算法的特性有了更深入的了解,同时也设计出了稳定性更好、实现简单的新算法。在此基础上,提出了基于小波的去噪方法。讨论了二维图像上非线性各向同性和各向异性扩散的局部(半)解析格式的构造和性质,并对三维情况进行了扩展。
课程简介: Nonlinear diffusion filtering has proven its value as a versatile tool for structure-preserving image denoising. Among the most interesting methods of this class are tensor-driven anisotropic diffusion as well as singular isotropic diffusion filters like total variation flow. For different reasons, devising good numerical algorithms for these filters is challenging. A spatial discretisation transforms nonlinear diffusion partial differential equations into systems of ordinary differential equations. Their investigation yields insights into the properties of diffusion-based algorithms but leads also to the design of new algorithms with favourable stability properties which are at the same time simple to implement. Moreover, interesting links to wavelet-based denoising methods are established in this way. The talk focusses on the construction and properties of locally (semi-)analytic schemes for nonlinear isotropic and anisotropic diffusion on 2D images, with extensions to the 3D case.
关 键 词: 图像扩散滤波; 局部解析
课程来源: 视频讲座网
最后编审: 2020-06-07:王勇彬(课程编辑志愿者)
阅读次数: 77