Multifocus image fusion based on Uniform Discrete Curvelet Transform

Fuzhen Zhu, Bing Zhu, Aiping Jiang, QunDing
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引用次数: 3

Abstract

A novel multi-focus image fusion method based on Uniform Discrete Curvelet Transform (UDCT) is proposed to overcome conventional muti-scale analysis image fusion shortcomings, such as high data redundancy ratio, complicated structure and poor performance, etc. First, UDCT is applied to the multi-focus images and subband coefficients of multi-scales and multi-directions are obtained. Then, different fusion rules are used for high-low frequency coefficients respectively. i.e. high frequency coefficients are fused by rules of local energy, and low frequency coefficients are fused by rules of local average gradient. Finally, Inverse Uniform Discrete Curvelet Transform (IUDCT) is applied to the new high-low frequency coefficients, and the fused result image is obtained. Simulation results show that the proposed UDCT images fusion method is superior to other related multi-scale analysis image fusion methods in subjective visual effect and objective evaluation parameters.
基于均匀离散曲线变换的多聚焦图像融合
针对传统多尺度分析图像融合存在数据冗余率高、结构复杂、性能差等缺点,提出了一种基于均匀离散曲线变换(UDCT)的多焦点图像融合方法。首先,将UDCT应用于多聚焦图像,得到多尺度、多方向的子带系数;然后,分别对高低频系数采用不同的融合规则。即高频系数采用局部能量规则融合,低频系数采用局部平均梯度规则融合。最后,对新的高低频系数进行反均匀离散曲线变换(IUDCT),得到融合的结果图像。仿真结果表明,所提出的UDCT图像融合方法在主观视觉效果和客观评价参数方面都优于其他相关的多尺度分析图像融合方法。
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