About this Research Topic
In recent years, lots of earth observation satellites have been launched. In the meantime, Unmanned aerial vehicle (UAV) development has also produced an affordable and practical tool for imaging landscapes. The achievements of satellites and UAVs have made it simpler than ever to collect enough optical/spectral images. To fully utilize these data, it is essential to research spectral image processing techniques such as compression, denoising, resolution enhancement, and dehazing of images. Additionally, these data can be applied in a variety of applications, including monitoring, change detection, land cover classification, and disaster management. However, the application of spectral images has not been researched sufficiently. As a result, we aim to present recent approaches to spectral image processing and analysis, particularly those relying on deep learning.
The contributions to this Research Topic are expected to address: 1) improvement of the quality of spectral images for perception; 2) the generalization of deep learning methods for spectral image processing and analysis; 3) few-shot learning for spectral image processing and analysis.
Specifically, we would like to address the following topics, but not limited to:
•Spectral image enhancement, including image deraining, image denoising, and image super-resolution;
•Multi-sensor data fusion, such as multispectral and panchromatic image fusion, multispectral and hyperspectral image fusion;
•Hyperspectral image classification;
•Image registration;
•Change detection;
•Object detection;
•Hyperspectral image unmixing;
•The generalization of deep learning methods for spectral image processing and analysis.
The contributions to this Research Topic are expected to address: 1) improvement of the quality of spectral images for perception; 2) the generalization of deep learning methods for spectral image processing and analysis; 3) few-shot learning for spectral image processing and analysis.
Specifically, we would like to address the following topics, but not limited to:
•Spectral image enhancement, including image deraining, image denoising, and image super-resolution;
•Multi-sensor data fusion, such as multispectral and panchromatic image fusion, multispectral and hyperspectral image fusion;
•Hyperspectral image classification;
•Image registration;
•Change detection;
•Object detection;
•Hyperspectral image unmixing;
•The generalization of deep learning methods for spectral image processing and analysis.
Keywords: deep learning, multispectral image processing, hyperspectral image processing, image enhancement, image fusion, hyperspectral image unmixing, image classification.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
