利用方向熵进行边缘滤波

Arijit K. Das, Prasenjit K. Mitra, Swaroop Ghosh, Asok K. Ray
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引用次数: 1

摘要

本文引入了方向熵的概念,用于量化属于边缘的像素的倾向。像素上的强度变化是作为对数函数在所有可能方向上的积分来测量的,该方向表示该点附近强度变化的异质性。这与传统的边缘滤波不同,传统的边缘滤波使用散度算子来考虑所有可能方向之间的最大强度变化。在我们的实验中发现,所提出的熵滤波器为许多基准图像提供了视觉上优越的边缘
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edge Filtering Using Orientation Entropy
The paper introduces the concept of orientation entropy for quantifying the propensity of a pixel belonging to the edge. Intensity variation at a pixel is measured as an integral of a logarithmic function over all possible direction which represents the heterogeneity of intensity variation in the neighborhood of that point. This is unlike traditional edge filters which uses divergence operator considering the maximum intensity variation among all possible directions. The proposed entropic filter is found to provide visually superior edges for a number of benchmark images considered in our experiments
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