Fig. 1. (a) Principle scheme of proposed color ghost imaging and (b) its sampling model.

Fig. 2. Illustration of non-local self-similarity in the spatial domain for a single-wavelength image and in the spectral domain between two wavelength images.

Fig. 3. Simulation results of three reconstruction algorithms in the case of detection $\mathrm{SNR}=30\mathrm{dB}$ and k$=10,000$. The first row is the object and their corresponding RGB images. The second row is the results of GISC_R. The third row is the results of GISC. The fourth row is the results of GISCNL. (c) The PSNR of reconstruction results in different reconstruction algorithms. The last column is the average processing time.

Fig. 4. Effect of measurement number k on the reconstruction quality when the detection $\mathrm{SNR}=30\mathrm{dB}$. The first row is the results of GISC_R. The second row is the results of GISC. The third row is the results of GISCNL. (a)–(f) Corresponding reconstruction results when the measurement number k is 4000, 6000, 8000, 10,000, 12,000, and 14,000, respectively. ($g$) The curve of PSNR versus k.

Fig. 5. Influence of detection SNR on the reconstruction quality when k$=10,000$. The first row is the results of GISC_R. The second row is the results of GISC. The third row is the results of GISCNL. (a)–(f) Corresponding reconstruction results when the detection SNR is 15 dB, 20 dB, 25 dB, 30 dB, 35 dB, and 40 dB, respectively. (g) The curve of PSNR versus detection SNR.