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Most pansharpened images from existing algorithms are apt to present a tradeoff relationship between the spectral preservation and the spatial enhancement. In this letter, we developed a hybrid pansharpening algorithm based on primary and secondary high-frequency information injection to efficiently improve the spatial quality of the pansharpened image. The injected high-frequency information in our algorithm is composed of two types of data, i.e., the difference between panchromatic and intensity images, and the Laplacian filtered image of high-frequency information. The extracted high frequencies are injected by the multispectral image using the local adaptive fusion parameter and postprocessing of the fusion parameter. In the experiments using various satellite images, our results show better spatial quality than those of other fusion algorithms while maintaining as much spectral information as possible.