Journal Article10.1117/1.JRS.15.042603
Study on ground object classification based on the hyperspectral fusion images of ZY-1(02D) satellite
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TL;DR: This work explores fusing the hyperspectral image with panchromatic and multispectral images captured by sensors onboard ZY-1 (02D) to obtain high-spatial-resolution and high-spectral-resolution images.
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Abstract: Spaceborne hyperspectral images are expected to have abundant applications in various fields, particularly in the quantitative observation of the Earth. However, the problem of low spatial resolution has limited their effectiveness to some extent. There are urgent needs for high-spatial-resolution hyperspectral images. We explore fusing the hyperspectral image with panchromatic and multispectral images captured by sensors onboard ZY-1 (02D) to obtain high-spatial-resolution and high-spectral-resolution images. Four approaches to obtain the final high-spatial-resolution hyperspectral image data are proposed, and six fusion methods are used. The fusion results were evaluated using quantitative indicators and classification performance, and image quality greatly improved after fusion. The fusion approach that used multispectral image data as an intermediate layer twice in the fusion process obtained the best fusion effect, and this was verified by both quantitative and application evaluation results. This provides an effective approach to obtain a high-quality, high-spatial-resolution hyperspectral image using the combination of panchromatic, multispectral, and hyperspectral images acquired by the sensors onboard ZY-1(02D).
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Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring
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Hyperspectral Image Super-Resolution Network Based on Cross-Scale Nonlocal Attention
TL;DR: Wang et al. as mentioned in this paper designed cross spectral-scale and shift-window based cross spatial-scale non-local attention networks (CSSNet) to fuse the LRHSI and HRMPI.
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Hyperspectral and Panchromatic Images Fusion Based on the Dual Conditional Diffusion Models
Shuangliang Li,Siwei Li,Lihao Zhang +2 more
TL;DR: A dual conditional diffusion models-based fusion network (DCDMF) to obtain the fused HRHSI and shows the superiority of this method over several state-of-the-art (SOTA) methods.
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Unmixing-Based PAN-Guided Fusion Network for Hyperspectral Imagery
TL;DR: Zhang et al. as discussed by the authors proposed a PAN-guided fusion network (Pgnet) to fuse the low spatial resolution HSI and the panchromatic (PAN) image with inverse features to get the high-resolution HSI (HR-HSI).
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Unmixing-Based PAN-Guided Fusion Network for Hyperspectral Imagery
TL;DR: Zhang et al. as discussed by the authors proposed a pan-guided fusion network (Pgnet) to fuse the low spatial resolution hyperspectral image (LR-HSI) and the panchromatic image (PAN) with inverse features to get the high-resolution HSI.
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