Research on crop area estimation based on super-resolution reconstruction of remote sensing videos

Aoxiang Yang; Jingli Wang; He Tai

doi:10.1117/12.3025848

8 April 2024 Research on crop area estimation based on super-resolution reconstruction of remote sensing videos

Aoxiang Yang, Jingli Wang, He Tai

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130903G (2024) https://doi.org/10.1117/12.3025848
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

To meet the needs of farmland surveys and area calculations in agricultural insurance claims, “Jilin-1” satellite video data was used for crop area calculations. Firstly, a set of video super-resolution reconstruction techniques was designed to address the issue of low-resolution video from the satellite. The Walsh-Hadamard transform and deep learning techniques were used to achieve super-resolution reconstruction of the satellite video. Secondly, the reconstructed data was used for crop area calculations. The experimental results showed that the Walsh-Hadamard transform and deep learning techniques can achieve good super-resolution reconstruction of satellite video, and the loss rate in crop area calculation using “Jilin-1” satellite data is within 0.23%, which meets the requirements of area calculation in agricultural insurance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Aoxiang Yang, Jingli Wang, and He Tai "Research on crop area estimation based on super-resolution reconstruction of remote sensing videos", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130903G (8 April 2024); https://doi.org/10.1117/12.3025848

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KEYWORDS

Super resolution

Video

Image processing

Remote sensing

Image restoration

Reconstruction algorithms

Satellites

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