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A Comprehensive Study on Computational Pansharpening Techniques for Remote Sensing Images

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Abstract

Real-time remote sensing imaging systems require high spatial resolution multispectral images. However, the remote sensing images obtained from a single satellite sensor do not provide a significant amount of information. Therefore, pansharpening techniques are desirable to provide high spatial resolution multispectral images. The hyperspectral pansharpening techniques are used to fuse the hyperspectral (HS) and the panchromatic (PAN) images to obtain an HS image with a significant amount of spatial and spectral information. The main objective of this paper is to provide a comprehensive review of the pansharpening techniques. Various categories of pansharpening techniques are also discussed. This paper provides three different summaries: initially, the conceptual aspects of pansharpening techniques are discussed. Thereafter, the comparative analyses are performed to evaluate the benefits and shortcomings of the existing pansharpening techniques. Finally, challenges and opportunities for future research in the field of pansharpening are discussed.

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Authors and Affiliations

  1. Chandigarh University, Gharuan, India

    Gurpreet Kaur & Kamaljit Singh Saini

  2. School of Engineering and Applied Sciences, Bennett University, Greater Noida, India

    Dilbag Singh & Manjit Kaur

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  1. Gurpreet Kaur
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  2. Kamaljit Singh Saini
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Correspondence to Dilbag Singh.

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Kaur, G., Saini, K.S., Singh, D. et al. A Comprehensive Study on Computational Pansharpening Techniques for Remote Sensing Images. Arch Computat Methods Eng 28, 4961–4978 (2021). https://doi.org/10.1007/s11831-021-09565-y

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