Intelligent Hyperspectral Image Compression Using Machine Learning
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 347
Special Issue Editor
Interests: machine learning; data compression; signal and image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Hyperspectral imaging technologies have been widely used in many remote sensing applications, resulting in large quantities of hyperspectral image datasets. Efficient acquisition, storage, and transmission of these massive image datasets becomes very challenging, especially for many onboard applications with severely constrained computing resources and communication bandwidths. Therefore, data compression techniques play a crucial role in the development of hyperspectral imaging techniques. Traditional data compression techniques provide either lossy, near lossless or strictly lossless compression on the data by identifying and using structures that exist in data of limited sizes (e.g., in individual images). Recent advancements in machine learning and artificial intelligence in general offer exciting new opportunities for compression algorithms to become “smarter” and thus more efficient, by learning and discovering structures existing in massive datasets with ever-increasing sizes.
This Special Issue is devoted to novel compression techniques for hyperspectral image data using machine learning. We solicit your contributions addressing applications of machine learning to hyperspectral data compression based some of the following methods:
- Statistical machine learning
- Supervised machine learning
- Unsupervised machine learning
- Semisupervised machine learning
- Reinforcement machine learning
- Transfer learning
- Active learning
- Online learning
- Other machine learning methods
Guest Editor
Manuscript Submission Information
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Keywords
- hyperspectral image
- data compression
- onboard compression
- machine learning
- deep learning
- neural network
- artificial intelligence
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