Advancement in Multispectral and Hyperspectral Pansharpening Image Processing

Dear Colleagues,

In the field of remote sensing and geographic information systems (GISs), the availability of high-resolution images is generally desirable, but not always viable. Typically, satellites collect different types of data from multiple sensors, such as RGB images in addition to spectral data. While RGB data are typically high-resolution, the spectral information used for different types of analysis is of a much lower resolution. In this context, data fusion techniques such as image pansharpening have become essential techniques to improve the spatial resolution of images.

The interest of the signal processing research community in this type of image processing has grown significantly in recent years, with an increasing number of papers presenting algorithms, surveys, and datasets for image pansharpening. In particular, deep learning techniques have emerged as the most promising solution for this task. Despite the great increase in the number of works presented in the state of the art, there are still unsolved problems and different horizons to be explored, from the study of the impact of such techniques in real applications to the extension of existing approaches from, for example, multispectral to hyperspectral data.

The Special Issue on “Advancement in Multispectral and Hyperspectral Pansharpening Image Processing” aims to collect the latest advances, methods, and applications in the field of pansharpening. It aims to explore innovative algorithms, machine learning, and deep learning approaches, and their practical implementations that push the boundaries of image fusion technology. Researchers will gain valuable insights into how these techniques can be used to enhance image analysis and improve task-driven data interpretation in various scientific and commercial domains. This collection of papers will not only highlight significant theoretical contributions, but will also showcase real-world applications, demonstrating the transformative potential of pansharpening in modern image processing.

Topics of interest in this Special Issue include, but are not limited to:

• New algorithms for multispectral and/or hyperspectral image pansharpening;
• The collection of new datasets for image pansharpening or related applications;
• The creation of new synthetic datasets for image pansharpening or related applications;
• The real-world applications of pansharpening algorithms (e.g., digital soil mapping);
• The application of pansharpening techniques to other tasks such as image classification, soil feature extraction, and environmental monitoring.

Dr. Simone Zini
Dr. Mirko Paolo Barbato
Dr. Flavio Piccoli
Guest Editors

Manuscript Submission Information

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• deep learning
• image fusion
• image sharpening
• pansharpening
• hyperspectral imaging
• multispectral imaging
• remote sensing