基于静态小波分析的高分辨率影像融合

研究了正交小波变换（MALLAT）与静态小波变换（SWT）改进的高分辨率影像融合方案。以QUICKBIRD影像为例，进行融合实验，并与标准IHS及BROVEY融合方案进行对比。采用信息熵、标准差指标对影像融合前后的信息量进行比较，选择平均值、相关系数、标准偏差指数进行光谱特征量化评价，采用细节信息相关性对融合高分辨针对ETM+全色波段与多光谱波段进行实验分析，结果表明小波变换融合算法总体优于传统融合算法，并能较好的保持光谱特性。

High Resolution Image Fusion Based on Stationary Wavelet Transform

Improvement of high resolution image fusion by Mallat algorithm for orthogonal wavelet transform and stationary wavelet transform（SWT）was studied.With QUIKBIRD image as example, fusion test was made and compared with standard HIS and BROVEY methods.Comparison was made on the information volumes of the images before and after the fusion by using the indexes of information entropy and standard variation.Average value, correlation coefficient and standard bias index were used in the quantitative evaluation.Analysis was made on panchromatic band and multi-spectral band by using the correlation of detailed information with high resolution of fusion.The results indicate that wavelet transform fusion algorithm is on the whole better than the conventional ones and can well keep the spectral characteristics.