摘要
针对融合规则不能真实反映观察者视觉感知特点的问题,提出一种异源图像多尺度融合算法。应用视觉注意机制,计算异源图像间的视觉显著度匹配系数,并根据这一系数对小波变换近似系数进行自适应融合,在小波细节系数融合中使用带有方向连续性检查的选大值方法,采用视觉显著度差对融合算法的视觉保持一致性进行评价。测试结果表明,与传统算法相比,该算法在客观性能指标和主观视觉一致性方面都有所提高。
A Visual Attention Mechanism（VAM）based multi-scale image fusion algorithm is proposed in this paper,which tries to overcome the inconformity between fusion rules and observer′ s visual characteristics. Visual saliency matching coefficients based on visual attention mechanism are computed and employed in Wavelet Transform（WT）approximate coefficient fusion. In WT detail coefficient fusion,select-max rule with directional consistency checking is used. A fusion performance evaluating method based on the comparison of visual saliency is proposed to measure visual consistency between source images and fused results. Experimental results demonstrate the superiority of the proposed algorithm in terms of subjective visual similarity and objective quantization comparison.
出处
《计算机工程》
CAS
CSCD
北大核心
2015年第3期247-252,共6页
Computer Engineering
基金
国家自然科学基金资助项目(61274021)
关键词
异源图像融合
视觉注意机制
视觉一致性
视觉显著度
多尺度融合算法
different-source image fusion
Visual Attention Mechanism（VAM）
visual consistency
visual saliency
multi-scale fusion algorithm
