A NEW FUSION METHOD FOR REMOTE SENSING IMAGES BASED ON SALIENT REGION EXTRACTION

The goal of the remote sensing image fusion is to inject the detail information extracted from panchromatic (PAN) images to multispectral (MS) images with minimized spectral distortion. However, different regions in the image may practically have different demands on the spatial and spectral resolution. In this paper, a new fusion method for remote sensing images based on salient region extraction is proposed. By introducing the hybrid visual saliency analysis, information in the PAN and MS image are automatically partitioned into two categories: salient and non-salient regions. Then, a sub-region fusion strategy is applied to fuse the non-salient and salient regions respectively. For non salient regions, such as farmland and mountains, the wavelet transform is used in the process of spatial infusion to suppress spectral distortion. As for salient regions like residential areas, the windowed IHS transform is carried out for its merits of effective integration of spatial and spectrum information. Experimental results demonstrate that our proposal achieves a better balance between spatial injection and spectral maintenance in different regions.