S2A: Wasserstein GAN with Spatio-Spectral Laplacian Attention for Multi-Spectral Band Synthesis
| Autor: | S. Manthira Moorthi, Indranil Misra, Litu Rout, Debajyoti Dhar |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Intersection (set theory) Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Image and Video Processing (eess.IV) Stability (learning theory) Computer Science - Computer Vision and Pattern Recognition Pattern recognition Function (mathematics) Electrical Engineering and Systems Science - Image and Video Processing Field (computer science) Norm (mathematics) FOS: Electrical engineering electronic engineering information engineering Artificial intelligence Scale (map) business Laplace operator |
| Zdroj: | CVPR Workshops |
| Popis: | Intersection of adversarial learning and satellite image processing is an emerging field in remote sensing. In this study, we intend to address synthesis of high resolution multi-spectral satellite imagery using adversarial learning. Guided by the discovery of attention mechanism, we regulate the process of band synthesis through spatio-spectral Laplacian attention. Further, we use Wasserstein GAN with gradient penalty norm to improve training and stability of adversarial learning. In this regard, we introduce a new cost function for the discriminator based on spatial attention and domain adaptation loss. We critically analyze the qualitative and quantitative results compared with state-of-the-art methods using widely adopted evaluation metrics. Our experiments on datasets of three different sensors, namely LISS-3, LISS-4, and WorldView-2 show that attention learning performs favorably against state-of-the-art methods. Using the proposed method we provide an additional data product in consistent with existing high resolution bands. Furthermore, we synthesize over 4000 high resolution scenes covering various terrains to analyze scientific fidelity. At the end, we demonstrate plausible large scale real world applications of the synthesized band. Computer Vision and Pattern Recognition (CVPR) Workshop on Large Scale Computer Vision for Remote Sensing Imagery |
| Databáze: | OpenAIRE |
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