摘要
针对小波变换的特点,对传统的小波能量法进行改进。实现了对融合结果由粗到细地分析,评价融合算法的优劣,通过各层的小波能量分布可以进一步选择小波融合的分解层数,预测融合结果。选取常见的小波函数——Haar小波作为图像融合的小波基函数,在点对点的融合策略下进行图像的融合实验,并利用改进后的小波能量法WE2对融合结果进行评价。
The traditional method of wavelet energy is improved as WE2.The new method WE2 can according to characteristics of wavelets analyze an image fusion incrementally; valuate an algorithm of wavelet for image fusion; select the number of wavelet layers according to the distribution of wavelet energy; forecast the result of image fusion.The authors selects commonly wavelets functions——Haar as mother-wavelets functions for image fusion .The strategy of image fusion is based on pixel to pixel. The improved method of wavelet energy WE2 is used to evaluate the image fusions.
出处
《武汉理工大学学报》
CAS
CSCD
北大核心
2005年第1期70-73,共4页
Journal of Wuhan University of Technology
基金
国家自然科学基金(60475031).
