Balancing Colors of Nonoverlapping Mosaicking Images With Generative Adversarial Networks

Remote sensing images of different moments or sensors can be stitched together to produce a new image under uniform geographic coordinate systems, where the overlapping areas were needed for color harmony. In this letter, a reference-based mosaicking method is proposed for images either with or with...

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Veröffentlicht in:IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser: Ma, Yaobin, Wei, Jingbo, Huang, Xiangtao
Format: Artikel
Sprache:eng
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Zusammenfassung:Remote sensing images of different moments or sensors can be stitched together to produce a new image under uniform geographic coordinate systems, where the overlapping areas were needed for color harmony. In this letter, a reference-based mosaicking method is proposed for images either with or without overlapping areas. The new method introduces a low-resolution image for spectral reference that spans all the mosaicking scope. A generative adversarial network is harnessed for color harmony, which transfers all the mosaicking images to the time of the reference image for further stitch with the graph cut and pyramid gradient methods. The proposed method is compared with three color harmony methods or tools by mosaicking the red, green, and blue bands of Landsat-8 images with MODIS as the reference. The digital evaluations demonstrate that the new method outweighs other methods regarding radiometric and spectral fidelity.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2021.3126261