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基于有理数阶偏微分的图像增强新模型
引用本文:蒋伟,李小龙,刘亚威.基于有理数阶偏微分的图像增强新模型[J].四川大学学报(自然科学版),2016,53(1):47-53.
作者姓名:蒋伟  李小龙  刘亚威
作者单位:重庆交通大学理学院;重庆交通大学理学院;重庆邮电大学自动化学院
基金项目:国家自然科学基金资助项目(61004118, 11071266); 重庆市自然科学基金资助项目(CSTC2012JJA1164)
摘    要:为了在锐化图像边缘的同时增强纹理细节特征,结合分数阶与整数阶微积分理论,推导出全新的有理数阶微分,从而在空间域构建了基于有理数阶偏微分的图像增强模型,并利用有理数阶偏微分掩模算子实现增强模型的数值计算.实验结果表明,该方法对图像可以得到连续变化的增强效果,不仅图像纹理得到很好的增强,图像边缘增强效果也比分数阶微分方法有所提高.客观上,借助实验对特征评价参数进行数据统计,结果显示新模型融合了整数阶微分与分数阶微分各自的优点,弥补了各自的不足,很好地达到了图像增强的目的.

关 键 词:图像增强    分数阶微分    有理数阶偏微分    信息熵    平均梯度
收稿时间:2014/12/14 0:00:00
修稿时间:2015/3/21 0:00:00

Image enhancement new model based on rational-order Partial Differential
Institution:School of Science, Chongqing Jiaotong University;College of Automation, Chongqing University of Posts and Telecommunications;College of Automation, Chongqing University of Posts and Telecommunications
Abstract:In order to sharpen the image edge features while enhancing texture detail, the image enhancement model based on space rational order derivative was constructed by the differential expression of rational order partial differential, and the numerical of enhanced model was achieved using rational order partial differential mask operator. The experimental results showed that compared with the fractional order differential method , the image enhancement model can be obtained the effect of continuous variation, that not only enhanced image texture well, but also improved the edge enhancement effect. Objectively, using parameters of texture features for quantitative analysis and experimental verification shown that the new model combined the advantages of integer and fractional order differential to make up for their lack of own and achieved a good image enhancement results.
Keywords:Image enhancement  Fractional-order differential  Rational-order partial differential  Information entropy  Average gradient
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