Image Fusion Based on Immune Clone Selection and Wavelet GΓD Model

摘要：

The computation of relative Saliency in fused approximate images local area is the key of obtaining efficient image fusion coefficients. According to the statistical characteristic of wavelet approximate coefficients in fused image, wavelet Generalized Gamma Distribution(GΓD) model is built for capturing the distribution of approximate coefficients in local area. GΓD models parameters are estimated by Immune Clone Selection(ICS) algorithm derived from Evolutionary Computation thinking. The estimated parameters are applied in a new fusion strategy for obtaining the final fusion coefficients. Results clearly demonstrate the superiority of this new approach when compared to the methods such as traditional contrast pyramid(CP) and wavelet fusion methods in terms of image information entropy(IE) values, average gradient(AG) values and standard difference(STD) values.

关键词： image fusion immune clone selection wavelet GΓD model contrast pyramid

作者: Zeng Fanhua Fu Dongmei

作者单位: School of Information Engineering, University of Science and Technology Beijing, Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 976-979

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）