Real HSI-MSI-PAN image dataset for the hyperspectral/multi-spectral/panchromatic image fusion and super-resolution fields

TL;DR

This paper introduces a real hyperspectral, multispectral, and panchromatic image dataset to improve the credibility and fairness of hyperspectral image fusion research, addressing limitations of simulated datasets.

Contribution

The authors release a real, spatially registered HSI/MSI/PAN dataset and provide processing code, facilitating more accurate and fair evaluation of fusion algorithms.

Findings

Enables more realistic evaluation of fusion methods

Addresses inaccuracies in simulated datasets

Supports multi-modal image fusion research

Abstract

Nowadays, most of the hyperspectral image (HSI) fusion experiments are based on simulated datasets to compare different fusion methods. However, most of the spectral response functions and spatial downsampling functions used to create the simulated datasets are not entirely accurate, resulting in deviations in spatial and spectral features between the generated images for fusion and the real images for fusion. This reduces the credibility of the fusion algorithm, causing unfairness in the comparison between different algorithms and hindering the development of the field of hyperspectral image fusion. Therefore, we release a real HSI/MSI/PAN image dataset to promote the development of the field of hyperspectral image fusion. These three images are spatially registered, meaning fusion can be performed between HSI and MSI, HSI and PAN image, MSI and PAN image, as well as among HSI, MSI, and PAN image. This real dataset could be available at https://aistudio.baidu.com/datasetdetail/281612. The related code to process the data could be available at https://github.com/rs-lsl/CSSNet.