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12 April 2023 Reconstructing hyperspectral images from RGB images fused with multi-scale features
Juanning Zhao, Song Lin, Yi Zhao, Lianshan Sun
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Proceedings Volume 12565, Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022); 1256508 (2023) https://doi.org/10.1117/12.2661532
Event: Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022), 2022, Shanghai, China
Abstract
The Hyperspectral image (HSI) can provide spectral information on the surface of objects, and has been widely used in remote sensing imaging, medicine and other fields. Due to the high cost of hyperspectral imaging systems, reconstruction of hyperspectral images from RGB images has become a research hotspot in recent years, but the reconstruction accuracy of existing algorithms is relatively limited. Based on the Transformer network, this paper designs an MC-Transformer model that integrates multi-channel feature extraction, uses a multi-channel encoder based on pixel scrubbing to extract spectral and spatial dimension features of different scales, through designs a multi-scale fusion strategy to fuse features, and finally analyzes high-dimensional features information and reconstruction hyperspectral images by decoder. Experimental results show that the MRAE of the reconstruction results of this method can reach 0.1795, which is 39.1% and 23.6% higher than the HRNet and AWAN models, respectively.
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Juanning Zhao, Song Lin, Yi Zhao, and Lianshan Sun "Reconstructing hyperspectral images from RGB images fused with multi-scale features", Proc. SPIE 12565, Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022), 1256508 (12 April 2023); https://doi.org/10.1117/12.2661532
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KEYWORDS
RGB color model
Reconstruction algorithms
Hyperspectral imaging
Computer programming
Transformers
Feature extraction
Data modeling
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