| Issue |
E3S Web Conf.
Volume 223, 2020
Regional Problems of Earth Remote Sensing (RPERS 2020)
|
|
|---|---|---|
| Article Number | 02007 | |
| Number of page(s) | 6 | |
| Section | Models and Methods of Remote Sensing Data Processing | |
| DOI | https://doi.org/10.1051/e3sconf/202022302007 | |
| Published online | 21 December 2020 | |
Methodology for Developing Algorithms for Compressing Hyperspectral Aerospace Images used on Board Spacecraft
1 Toraighyrov university, Electrical Engineering and Automation Department, 140000 Lomov street 64, Kazakhstan
2 National research Tomsk state university, Institute of Applied Mathematics and Computer Science, 634050 Lenina avenu 36, Russia
The paper describes a method for constructing and developing algorithms for compressing hyperspectral aerospace images (AI) of hardware implementation for subsequent use in remote sensing Systems (RSS). The developed compression methods based on differential and discrete transformations are proposed as compression algorithms necessary for reducing the amount of transmitted information. The paper considers a method for developing compression algorithms, which is used to develop an adaptive algorithm for compressing hyperspectral AI using programmable devices. Studies have shown that the proposed algorithms have sufficient efficiency for use and can be applied on Board spacecraft when transmitting hyperspectral remote sensing data in conditions of limited buffer memory capacity and communication channel bandwidth.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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