两种改进小波算法的卫星多波段数据融合

本文采用两种改进的算法:基于HSV的小波融合算法(HSV-WT)、基于区域特征的自适应小波包融合算法(AWP)分别对多光谱LandSat TM数据与全色SPOT-5数据、TM数据与ERS-2的合成孔径雷达SAR数据进行融合.融合结果表明两种改进算法融合后的数据在保持光谱信息和提高空间细节信息两方面均得到提高.当应用两种方法对同一组数据进行处理时, AWP的性能参数优于HSV-WT.这两种算法相对传统小波算法,能克服对高频信息处理的缺陷,突破待融合数据的分辨率比值限制,实现分辨率之比非2n的数据融合.

Multi-Band Satellite Data Fusion Based on Two Improved Wavelet Algorithms

Two improved fusion algorithms have been constituted, wavelet fusion based on HSV color model(HSV-WT)and an Adaptive Wavelet Packet(AWP) based on region features, which were applied to processing satellite data,MultiSpectral(MS) LandSat TM & Panchromatic(P) SPOT-5, and LandSat TM MS & Synthetic Aperture Radar(SAR).The proposed HSV-WT & AWP algorithms enhance the fused image’s ability to express the spatial details while preserving spectral information of the MS data. Experimental results demonstrate that AWP performs better than HSVWT in fusing the same data. These two algorithms, compared with traditional wavelet algorithms, can help to overcome defects when processing high-frequency signals, and they are appropriate for fusing data if the ratios of spatial resolution between the two images to be fused are not in 2 n relationships.