## 3 Experimental Scheme and Analysis of Results
### Experimental Results and Cause Analysis
images obtained by CGI, BP, and TVAL3 algorithms still exists, but it is obvious that the reconstruction of the object becomes clearer, and it can be seen that the reconstruction effect of CGI and TVAL3 is still superior to that of BP, the reconstruction result from DL is more clearer than the object, and the quality of the image becomes better with the increase in the sampling rate. When the sampling rate is 37.5%, CGI, BP, and TVAL3 are also able to obtain the reconstructed object's image clearly, although the effect of BP is still not as good as that of CHI and TVAL3, but the background noise information is reduced significantly. The reconstructed image effect of the untrained DL is intuitively much larger than the other three algorithms, and the reconstructed image quality is better. Figure 8 shows a comparison of the PSNR of the four methods for reconstructing an image through a scattering medium using intensity information at different sampling rates. According to our proposed scheme, when the sampling rate is 12.5%, the PSNR of the reconstructed image using PSNR value of the reconstructed image by CGI algorithm is 8.21 dB, the PSNR value of the reconstructed image by BP algorithm is 8.22 dB, the PSNR value of the reconstructed image by TVAL3 algorithm is 10.31 dB, and the PSNR value of the reconstructed image by DL algorithm is 12.14 dB. When the sampling rate is 37.5%, the PSNR value of the reconstructed image using CGI algorithm is 9.67 dB, the PSNR value of the reconstructed image using BP algorithm is 9.06 dB, the PSNR value of the reconstructed image using TVAL3 algorithm is 12.28 dB, and the PSNR value of the reconstructed image using DL algorithm is 14.35 dB. Overall, as the sampling rate increases, the PSNR also increases, and our proposed method of combining SPI and ToF can effectively suppress the interference of the scattering medium on the target object and realize the reconstruction of the target object image. Gaussian noise is a random noise whose distribution follows a normal distribution (Gaussian distribution). In image processing, we can add Gaussian noise to an image to simulate a real-world noise situation. Gaussian noise is commonly used to test and evaluate the robustness of image processing algorithms. By adding noise to an image, we can check the algorithm's tolerance to noise and its effect on image quality. In order to highlight the ability of our proposed method to improve the resolution and image quality of the ToF camera, and also to demonstrate that our proposed method is also robust to the internal noise of the ToF camera and the environmental noise, we add Gaussian noise to the intensity information acquired by the ToF camera and process the image using our proposed scheme. Figure 7: Experimental results of reconstruction using the intensity images through the scattering media at different SRs. (**a**) ToF image, (**b**–**e**) the recovered images by CGI, BP, TVAL3, and DL. The SRs from left to right are 6.25%, 12.5%, 18.75%, 25%, 31.25%, and 37.5%. The experimental results of adding Gaussian noise are depicted in Figure 9, where we continue to employ four algorithms for image reconstruction at sampling rates of 6.25%, 12.5%, 18.75%, 25%, 31.25%, and 37.5%, respectively. Figure 9 displays the original intensity image acquired directly from the ToF camera without the addition of Gaussian noise, while Figure 9 exhibits the intensity image captured with Gaussian noise incorporated. Observing Figure 9c-f, it becomes apparent that CGI, BP, and TVAL3 only discern a blurred representation of the object when the sampling rate is below 12.5%. However, the untrained DL algorithm adeptly restores the object's image, even at substantially lower sampling rates, surpassing the image quality of the Gaussian noise-introduced Figure 9. At a 25% sampling rate, CGI, BP, and TVAL3 successfully reconstruct the object's image, although the DL algorithm outperforms them, albeit not to the same extent as at lower sampling rates.