Methodology for Developing Algorithms for Compressing Hyperspectral Aerospace Images used on Board Spacecraft

Author:

Sarinova Assiya,Zamyatin Alexander

Abstract

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.

Publisher

EDP Sciences

Reference13 articles.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Lossless Compression Algorithm of Hyperspectral Aerospace Images With Correlation and Bands Grouping;2022 International Conference on Smart Information Systems and Technologies (SIST);2022-04-28

2. Regression Approach to Lossles Compression Algorithm for Hyperspectral Images;2022 International Conference on Smart Information Systems and Technologies (SIST);2022-04-28

3. Development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations;E3S Web of Conferences;2021

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