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Hyperspectral image (HSI) with high spectral resolution often suffers fromlow spatial resolution owing to the limitations of imaging sensors. Imagefusion is an effective and economical way to enhance the spatial resolution ofHSI, which combines HSI with higher spatial resolution multispectral image(MSI) of the same scenario. In the past years, many HSI and MSI fusionalgorithms are introduced to obtain high-resolution HSI. However, it lacks afull-scale review for the newly proposed HSI and MSI fusion approaches. Totackle this problem,this work gives a comprehensive review and new guidelinesfor HSI-MSI fusion. According to the characteristics of HSI-MSI fusion methods,they are categorized as four categories, including pan-sharpening basedapproaches, matrix factorization based approaches, tensor representation basedapproaches, and deep convolution neural network based approaches. We make adetailed introduction, discussions, and comparison for the fusion methods ineach category. Additionally, the existing challenges and possible futuredirections for the HSI-MSI fusion are presented.

Recent Advances and New Guidelines on Hyperspectral and Multispectral Image Fusion