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机构地区:[1]北方工业大学理学院,北京100144 [2]北京林业大学理学院,北京100083
出 处:《计算机工程》2017年第4期263-268,276,共7页Computer Engineering
基 金:国家自然科学基金(61272026;61571046);澳门科技发展基金(097/2013/A3)
摘 要:V-变换在表达图像时可以通过增加V-系统基函数的数量得到图像由粗到细的多尺度特征描述,但是V-系统不适宜描述图像的方向特性。为此,根据Contourlet变换的多方向性特征,将V-变换和Contourlet变换结合起来,提出一种图像融合算法,得到图像的多尺度和多方向特征描述,并将之应用到多聚焦图像的融合中。改进数学工具,设计加权局域统计特征的频域系数融合方案,并选用能刻画系数相关性特点的高斯分布作为权值。实验结果表明,与基于小波变换、Contourlet变换以及小波-Contourlet变换的多分辨分析的融合算法相比,该算法融合后的图像在边缘细节处更加清晰,视觉效果更好,信息量、清晰度以及与待融合图像的相关程度等客观评价指标也得到改进。When the V-transform is used to express an image, a coarse to fine multi-scale feature description can be obtained by increasing the number of basis functions of the V-system. But the V-system is not suitable for describing the direction feature of images. As the Contourlet transform has multidirectional characteristics,this paper proposes an image fusion algorithm by combining the V-transform with the Contourlet transform to obtain multi-scale and multi-direction feature description, and applies it to the multi-focus image fusion. In addition to the improved mathematical tools, a fusion scheme of frequency domain coefficients with weighted local statistical characteristics is designed. The weights are chosen from a Gaussian distribution which can effectively depict the correlation of the coefficients. Experimental results show that the fused image obtained from the proposed algorithm has clearer edge details and better visual effect, and the proposed algorithm improves some objective evaluation indexes, such as amount of information ,clarity and correlation degree with the original images,compared with multi-resolution fusion algorithms based on wavelet transform, Contourlet transform and Contourlet-wavelet transform.
关 键 词:图像融合 V-系统 V-变换 CONTOURLET变换 多聚焦图像 高斯分布
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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