SBHSR: single-band super-resolution method for hyperspectral images based on blind degradation and fusion of auxiliary band

Figures & data

Figure 1. The framework of SBHSR network.

Figure 2. Estimation H moudule structure.

Figure 3. Mul-Encoder structure.

Figure 4. DRAM structure.

Figure 5. SAM structure.

Figure 6. ResBlock structure.

Figure 7. Comparison of three sets (a–c) of grayscale image details for the 55th band reconstructed from Pavia-Center data.

Figure 8. The detailed image of the 55th band of Pavia-Center data.

Figure 9. Details of the doubled super-resolution (a) (b) of 12th band in the original image of OHS data.

Table 1. Quantitative evaluation Pavia-Center dataset.

Method	PSNR↑	SSIM↑
Real-ESRGAN	29.7890	0.8589
KXNet	29.6020	0.8784
DASR	33.6030	0.9489
SFCSR	33.5660	0.9247
SBHSR (ours)	33.9570	0.9524

Table 2. The no-reference image evaluation metrics.

Method	NIQE↓	PIQE↓
Bicubic	6.4891	100
Real-ESRGAN	6.1239	39.8078
IKC	5.3861	51.3632
DASR	5.1073	48.4600
SFCSR	4.7071	46.8275
SBHSR (ours)	5.0897	41.2310

Figure 10. Absolute error maps of the reconstructed hyperspectral images.

Figure 11. Spectral curve comparison chart.

Data availability statement

Some or all data, models, or code generated or used during the study are available from the corresponding author by request.