Fusion of RISAT-1 SAR Image and Resourcesat-2 Multispectral Images Using Wavelet Transform

This paper presents a pixel level wavelet-based approach to fuse synthetic aperture radar (SAR) imagery with multispectral (MS) imagery. Image fusion combines information from two or more images to generate a new image, which is rich in information. Due to complementary nature of SAR and multispectral imagery, fusion of these images is of significant interest in the field of remote sensing. The primary objective of this work is to enhance spatial information in multispectral images by injecting structural information derived from SAR image. Due to negative correlation between SAR and multispectral data, conventional component substitution methods face the problem of spectral distortion in the fused image. Wavelet based fusion approaches overcome this problem due to excellent localization in spatial and frequency domain. Here, different wavelet-based fusion rules are applied for fusion of SAR and multispectral images. Fusion rules applied to fuse approximate sub-bands and detail sub-bands of these images consider spectral dis-similarity between them. Results are evaluated visually, as well as using standard quality metrics and are compared with component substitution fusion techniques namely, principal component analysis and generalized IHS transform. Trade-off between spectral and spatial quality of fused image has been observed while fusing SAR and multispectral images.