Dear Colleagues,

As one of the fastest-developing research areas in image processing, hyperspectral imaging (HSI) has facilitated a wide range of applications. These span from remote sensing-based mining, precision agriculture, and environmental monitoring, to more industry-based applications, including food/drink, smart manufacturing and pharmaceutical quality inspection/grading, medical applications, and even artwork authentication. With the increasing demands from numerous industrial fields, more efficient and effective algorithms, as well as data analysis techniques, that can handle vast amounts of data for hyperspectral imagery under various conditions, become more pressing.

Particular challenges in the processing of hyperspectral data are how to deal with the high-volume data, yet with limited spatial or spectral (for multispectral systems) resolutions, especially for reducing the data, enhancing the (spatial) resolution and fusion of the spatial and spectral information for improved data prediction (i.e., classification and regression analysis). Many algorithms and techniques have been proposed and are continuously needed for addressing such challenges.

The goal of this Special Issue is to provide a premier forum for researchers working on the aforementioned HSI challenges and related applications, as well as to provide an important opportunity for multidisciplinary development. Future trends and perspectives will be a particular focus of this Special Issue. The topics of interest include, but are not limited to, the following:

• New sensors and sensing techniques;
• Optimized data sampling and acquisition;
• Techniques for effective pre-processing (e.g., denoising/deblurring and data compression);
• Sparse representation and data reduction;
• Feature transform and feature extraction;
• Band selection and optimization;
• Spectral unmixing and super-resolution;
• Visualization and retrieval;
• New techniques for data classification, target detection, and so on;
• Emerging applications in precision agriculture, nondestructive inspection, urban planning, medical imaging, and so on.

Dr. Jinchang Ren
Prof. Stephen Marshall
Dr. Wenzhi Liao
Prof. Zheng Wang
Guest Editors

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• Hyperspectral imaging
• Band selection
• Data classification
• Compressed sensing
• Deep learning
• Spatial–spectral fusion
• Sparse representation
• Remote sensing
• Precision agriculture
• Nondestructive inspection
• Data visualization…