Thin cloud image technology of LLNet-based enhanced optimal remote sensing satellite

Peng Liu; Yan Wang; Xiangli Meng; Wenjun Dong; Jin Zhang

doi:10.1117/12.2656094

12 January 2023 Thin cloud image technology of LLNet-based enhanced optimal remote sensing satellite

Peng Liu, Yan Wang, Xiangli Meng, Wenjun Dong, Jin Zhang

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 125091T (2023) https://doi.org/10.1117/12.2656094
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

This paper proposes improved low-light net (LLNet) parameters based on the imaging features of optical remote sensing satellites, which are built on the conventional LLNet low-light image enhancement network. The network can be better adapted to the characteristics of thin cloud optical remote sensing satellite images by using the improved network parameters for denoising auto-encoder (DA) layer design, data training, and improvement effect evaluation of LLNet. This will enable the network to extract data features from the images and carry out adaptive image enhancement without over amplifying the highlighted areas. A set of specially produced high-definition satellite images is used as the experimental data set to validate the network parameter design experimentally, and the results show that the proposed improved network parameters can effectively enhance the simulated and real thin cloud optical remote sensing satellite images and can eliminate/diminish the serious influence of thin clouds on the features to a certain extent. After the enhancement of the simulated thin cloud image, its structural similarity with the reference image is improved by about 300%. Its subjective enhancement effect is more obvious even for the real thin cloud image.

Citation Download Citation

Peng Liu, Yan Wang, Xiangli Meng, Wenjun Dong, and Jin Zhang "Thin cloud image technology of LLNet-based enhanced optimal remote sensing satellite", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 125091T (12 January 2023); https://doi.org/10.1117/12.2656094

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KEYWORDS

Image enhancement

Clouds

Satellite imaging

Remote sensing

Satellites

Image quality

Earth observing sensors

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