Multispectral to Panchromatic Image Fusion Based on Morphological Extended-Half-Gradient

Pansharpening refers to the fusion of remotely sensed multispectral and panchromatic images which are characterized by different levels of spectral–spatial resolutions and acquired for the same location by optical remote sensing satellite sensors. In this paper, we propose a pansharpening algorithm based on morphological extended-half-gradient. Popular quality metrics employing two assessment methods, namely reduced resolution assessment and full resolution assessment, are used for performance measurement. For validating the efficiency of the proposed algorithm, we compare its performance with that of morphological half-gradient-based fusion procedure and a few other popular image fusion algorithms. We also propose the best possible bias factor in the formulation of the proposed algorithm by experimentation on varied values. Three real datasets acquired by WorldView-4, SPOT-6 and QuickBird-2 are used in the experimentation. The results affirm that the proposed algorithm offers improved image fusion than using the morphological half-gradient. This successful demonstration of the proposed algorithm proves the potential of morphological image processing operations to be useful in the achievement of efficient pansharpening. This work also underlines the need for more computational efficiency in image fusion.