基于非向下采样contourlet的自适应图像融合算法  

Adaptive Image Fusion Algorithm Based on Nonsubsampled Contourlet Transform

作　　者：张海朝[1] 张芳芳[1] 孙士保[1] 王亚涛[1] 

机构地区：[1]河南科技大学电子信息工程学院,洛阳471003

出　　处：《计算机科学》2010年第8期262-265,共4页Computer Science

基　　金：国家自然科学基金项目(60475021);洛阳市科技攻关计划项目(0701041A)资助

摘　　要：针对融合后图像模糊现象,提出一种基于非向下采样contourlet的自适应图像融合算法。分析了轮廓波变换和非抽样轮廓波变换的原理,采用非向下采样contourlet对图像进行分解,依据低频变化设置阈值来调节低频变化率和均匀度在决策规则中所占的比例。当低频变化率之差高于阈值时,采用基于均匀度的融合规则;当低频变化率之差低于阈值时,采用基于变化率的融合规则。对于高频部分则采用高频系数对比度的处理策略。通过熵、相对误差和清晰度对实验结果进行了评价,结果表明,基于非向下采样contourlet的自适应融合算法取得了良好的融合效果。To solve the fuzzy phenomenon of fusion images, an adaptive image fusion algorithm based on nonsubsampled contourlet transform（NSCT） was proposed. The good properties of the contourlet transform and the nonsubsampled contourlet transform were discussed. After the original images were decomposed by NSCT, the low-frequency images were fused by the low-frequency changing rate and uniformity. When the changing rate difference between the low-fre- quency images was lower than the threshold, the changing rate was selected for making decisiom otherwise the unifom^ity was used to make decision. The high-frequency images were fused by the high frequency contrast to make decision. After the image was fused, the entropy, relative error and average gradient were used to evaluate the fusion performance. The results show the adaptive fusion algorithm based on the nonsubsampled contourlet transform（NSCT） obtains better fusion performance.

关 键 词：图像融合 NSCT 变化率 均匀度 对比度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]