Analysis of Spectral Characteristics Based on Optical Remote Sensing and SAR Image Fusion

Because of cloudy and rainy weather in south China, optical remote sensing images often can’t be obtained easily. With the regional trial results in Baoying,Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satellite multispectral remote sensing images. Based on the ARSIS strategy, using the wavelet transform and the Interaction between the Band Structure Model(IBSM), the research progressed the ENVISAT satellite SAR and the HJ-1A satellite CCD images wavelet decomposition, and low/high frequency coefficient reconstruction, and obtained the fusion images through the inverse wavelet transform.In the light of low and high-frequency images have different characteristics in different areas, different fusion rules which can enhance the integration process of selfadaptive were taken, with comparisons with the PCA transformation, IHS transformation and other traditional methods by subjective and the corresponding quantitative evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest.The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.