A NOVEL APPROACH FOR FUSION OF LOW RESOLUTION MULTISPECTRAL IMAGES IN REMOTE SENSING

Nonlinear decomposition methods comprise a choice to conventional approaches for facing the problem of data fusion. In this paper, we discuss the application of this methodology to a admired remote sensing area called pan sharpening, which consists in the fusion of a low resolution multispectral image and a high-resolution panchromatic image. We design a complete pan sharpening scheme based on the use of morphological half gradient operators and demonstrate the application of this algorithm through the comparison with the state-of-the-art approaches. Four data sets obtained by the different satellites are employed for the performance monitoring, testifying the effectiveness of the proposed method in producing top-class images with a setting independent of the specific sensor