改进的分数阶差分图像信息提取算法

Mingliang Hou, Yuran Liu, Yanglie Fu
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引用次数: 3

摘要

纹理和边缘信息对大多数自然图像的识别同样重要。针对现有的整数阶微分算子不能从图像中提取纹理信息的缺点,在解决分数阶微分算子漂移问题的基础上,开发了一种可以同时提取纹理和边缘信息的分数阶微分算法。实验结果表明,该算法不仅可以提取纹理信息,而且可以提取出比传统算法更多的边缘信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Improved Fractional Order Differential Image Information Extraction Algorithm
Texture and edge information are equally important to identification of most of natural images. In view of the weakness of the existing integer order differential operators that it can't extract texture information from the images, this study developed a fractional differential algorithm, which can extract texture and marginal information simultaneously, based on settlement of the drift problem of fractional differential operator. Experimental results showed that our algorithm can not only extract texture information but also extract more edge information than the traditional algorithms.
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