Title: Multispectral and hyperspectral image fusion: a systematic analysis and review with the state of art techniques

Authors: Balajee Maram; K. Suresh Kumar; Veerraju Gampala

Addresses: Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali 140055, Punjab, India ' Department of Information Technology, Saveetha Engineering College, Chennai, India ' Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India

Abstract: The fusion of multispectral images (MSI) and hyperspectral images (HSI) has been acknowledged as a promising method for performing HSI-MSI fusion, which is also an essential part of the precise recognition and cataloguing of the underlying materials. However, the HSI-MSI fusion needs high resolution images to perform precise analysis and decision-making. Numerous techniques were devised in the prior works that employed image fusion using HSI and MSI. This paper presents a complete survey of 80 papers using HSI-MSI fusion methodologies, which involve pan sharpening, subspace, artificial intelligence, deep learning, and hybrid models. In addition, thorough investigations are performed based on the year of publication, adapted methodology, datasets used, implementation tool, evaluation metrics, and values of evaluation metrics. Finally, the issues of existing methods and the research gaps considering conventional HSI-MSI fusion schemes are elaborated to obtain improved contributions for devising significant HSI-MSI fusion techniques.

Keywords: image fusion; deep learning; multispectral images; MSI; hyperspectral images; HSI; pansharpening.

DOI: 10.1504/IJBIC.2024.139277

International Journal of Bio-Inspired Computation, 2024 Vol.23 No.4, pp.214 - 224

Accepted: 12 Sep 2023
Published online: 28 Jun 2024 *

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