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引用次数: 2

摘要

提出了一种利用矢量样本排序的矢量滤波器的新推广方法。根据基于矢量距离和矢量角度的距离函数,可以区分矢量中值滤波器(VMFs)、矢量方向滤波器(vdf)和最后结合矢量空间中矢量样本的距离和角度的定向距离滤波器(ddf)。出于这个原因,一类ddf代表了一类广义的向量过滤器。然而,通过在DDF结构中引入权向量,所有上述滤波器,包括它们的加权结构,都可以表示为所提出的新型加权方向距离滤波器(wddf)的特殊情况。除了理论采集之外,所提出的wddf提供了很高的设计灵活性,与标准矢量滤波器类相比,这些滤波器的设计可以实现滤波器性能的显着改善。
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Another generalisation of vector filters
A new generalisation of vector filters utilising the ordering of vector samples is provided. According to a distance function based on vector distances and vector angles, it is possible to differentiate vector median filters (VMFs), vector directional filters (VDFs) and finally directional distance filters (DDFs) that combine both distance and angles of vector samples in the vector space. For that reason, a class of DDFs represents a generalised class of vector filters. However, it will be shown that by introducing the weight vector to a DDF structure, all the above-mentioned filters, including their weighted structures, can be expressed as special cases of the proposed new class of weighted directional distance filters (WDDFs). Besides the theoretical acquisition, the proposed WDDFs provide a high design flexibility and these filters can be designed to achieve a significant improvement of the filter performance in comparison with standard vector filter classes.
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