Fig. 1. Multi-spectral remote sensing imaging degradation model from high resolution images to low resolution images

Fig. 2. Statistics for dark channel values of high resolution images and low resolution images

Fig. 3. General flow of dark channel and cross channel based multi-prior combined multi-spectral super-resolution algorithm

Fig. 4. Comparison of reconstruction results of aerial remote sensing data. (a) Bicubic; (b) TVSR; (c) CASR; (d) DCSR; (e) CCSR; (f) MPSR

Fig. 5. Comparison of reconstruction results of aircraft remote sensing data. (a) Bicubic; (b) TVSR; (c) CASR; (d) DCSR; (e) CCSR; (f) MPSR

Fig. 6. Comparison of reconstruction results of MDSP data. (a) Bicubic; (b) TVSR; (c) CASR; (d) DCSR; (e) CCSR; (f) MPSR

Fig. 7. Multi-spectral images used in simulation experiment. (a) Original high resolution image; (b) low resolution image with 10 dB signal-to-noise ratio; (c) low resolution image with 25 dB signal-to-noise ratio; (d) low resolution image with 40 dB signal-to-noise ratio; (e) low resolution image with chromatic aberration

Table 1. Comparison of PSNRs of super-resolution algorithms with different noises or chromatic aberrations

Table 2. Comparison of SSIMs of super-resolution algorithms with different noises or chromatic aberrations