基于粒子群优化算法的像素级图像融合  

Image Fusion of the Pixel Level Based on Particle Swarm Optimization Algorithm

作　　者：章小龙[1] 

机构地区：[1]漳州师范学院计算中心,福建漳州363000

出　　处：《漳州师范学院学报（自然科学版）》2009年第2期37-40,共4页Journal of ZhangZhou Teachers College（Natural Science)

摘　　要：多传感器的像素级图像融合中,如果对源图像进行线性运算以得到融合图像,源图像的置信度取值一般只能由经验和个人主观感觉来确定,并不能得到令人满意的融合效果.本文针对这一问题提出了一种基于粒子群优化算法的像素级图像融合的算法.该算法可以根据融合的目的采用不同的融合指标,应用粒子群优化算法得到比较满意的融合图像.实验结果表明该算法优于其它的几种像素级图像融合算法.In the research of the multi-sensor image fusion of the pixel level, the fused image acquired by linear operation on source images, can not get the satisfactory fusion results, because the weight values of the source images all depend on experience and individual subjective sense. According to this problem, an image fusion algorithm of the pixel-level based on the PSO （Particle Swarm Optimization） is introduced in this paper. This algorithm uses different fusion index in term of different aim of the fusion to achieve a better effect of fusion. Experimental results show the algorithm outperforms other image fusion algorithms of the pixel level.

关 键 词：像素级图像融合 粒子群优化算法 融合指标 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]