Color correction of remote sensing images based on style transfer

Jiguang Dai; Wenhao Xu; Tengda Zhang; Jinsong Chen; NanNan Shi; Shaodong Xu

doi:10.1117/12.3032208

3 June 2024 Color correction of remote sensing images based on style transfer

Jiguang Dai, Wenhao Xu, Tengda Zhang, Jinsong Chen, NanNan Shi, Shaodong Xu

Proceedings Volume 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024); 131700Q (2024) https://doi.org/10.1117/12.3032208
Event: Third International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 2024, Wuhan, China

Abstract

Color distortion of remote sensing image is a common problem, and the color distortion of remote sensing image is not conducive to its subsequent interpretation. The existing color correction methods have problems such as poor correction effect and distortion of texture details. To solve these problems, this paper proposes an improved CAP-VSTNet style migration network. The proposed structure-color loss function can make the texture and color of the result close to the target image. The AdaIN adaptive normalization layer is introduced to improve the correction effect without increasing the calculation amount. Experiments on public datasets show that the proposed method outperforms other comparison methods in mean square error, peak signal-to-noise ratio, structural similarity and IL-NIQE(a completely blind image quality assessment method).

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

Citation Download Citation

Jiguang Dai, Wenhao Xu, Tengda Zhang, Jinsong Chen, NanNan Shi, and Shaodong Xu "Color correction of remote sensing images based on style transfer", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131700Q (3 June 2024); https://doi.org/10.1117/12.3032208

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KEYWORDS

Remote sensing

Distortion

Histograms

Education and training

Image segmentation

Reflection

RGB color model

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