Research map / Image generation / Image restoration
Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with CASSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | PSNR | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with DCD · Synthetic hyperspectral images from Columbia Multispectral Image Database | PSNR | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with SSCSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | PSNR | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with CASSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | SSIM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with DCD · Synthetic hyperspectral images from Columbia Multispectral Image Database | SSIM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with SSCSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | SSIM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with CASSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | SAM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with DCD · Synthetic hyperspectral images from Columbia Multispectral Image Database | SAM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of the competing restoration methods | Coded hyperspectral image restoration with SSCSI · Synthetic hyperspectral images from Columbia Multispectral Image Database | SAM | Helped |
| Use spectral and spatial non-local low-rank regularization instead of TV regularization | CASSI restoration · Real Ninja scene | visual quality | Helped |
| Use spectral and spatial non-local low-rank regularization instead of TV regularization | DCD restoration · Real Ninja scene | visual quality | Helped |
Closest papers by meaning
- A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration (NeurIPS 2021 · similarity 0.90)
- SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction (CVPR 2024 · similarity 0.87)
- Spectral Compressive Imaging via Chromaticity-Intensity Decomposition (NeurIPS 2025 · similarity 0.86)
- Improving Spectral Snapshot Reconstruction with Spectral-Spatial Rectification (CVPR 2024 · similarity 0.86)
- HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models (CVPR 2024 · similarity 0.86)
- FRN: Fractal-Based Recursive Spectral Reconstruction Network (NeurIPS 2025 · similarity 0.85)
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