## 6 Experimental Results and Discussion
### Performance Evaluation of DIFRT with Different BER  
In this test on DIFRT, the camera firstly captured three standard images inside the pipe. These images were converted into the test original gray image (size: \(256\times 256\) pixels, bit depth: 8 bits) in the PC. After DCT and quantization processing, the original digital image could be transformed into binary data in sequence. After data frame synthesis and PWM modulation, these binary data were loaded onto the light signal [48; 49; 50]. Through two relay transmission at a baud rate of 50 kbps, finally, the digital image frames were able to be reconstructed by decoding at the receiver. In this experiment, one important parameter BER was used to evaluate the performance of DIFRT. During the digital image transmission, the BER could inevitably exist, which had an immense impact on the final reconstruction of the digital image.  
As depicted in Figure 11, the leftmost column corresponds to the original images, and the right parts of this figure show the complete image received by the final receiver in the water and empty pipe after two signal relay transmission. For both AISRT and DIFRT methods, three image frames were captured and selected as experimental samples. It was evident that the image could be well reconstructed by the DIFRT method rather than the previous AISRT method. Figure 11 illustrates that DIFRT exhibited higher reconstruction performance considering the structure, brightness, similarity, and noise of final restored images. As further analyzed from Table 2, some statistical parameters such as PSNR, MSE, MAE, and SSIM of the reconstructed image in the final receiver have also been chosen as the criterion for evaluating image quality. Like AISRT method, the MATLAB calculation of these four parameters was also based on the 8 bit depth grayscale image, and therefore the performance comparison between DIFRT and AISRT was based on the same standard. In the water pipe, using DIFRT, the MSE could reach about 232.13-302.23, whereas the value was 21,992-22,829 with the AISRT method [51; 52; 53]. That means DIFRT has a stronger capability to deal with noise and interference caused by water absorption and scattering effects. This ability could be also reflected in the PSNR. The PSNR value after adopting the DIFRT method reached almost 24.473 which is almost five times the result obtained by utilizing the AISRT method. Although the SSIM value reached 0.90926 (in the water pipe) and 0.96146 (in the empty pipe), we could also observe that after the DIFRT approach was adopted, the reconstructed image structure and brightness was further improved compared with AISRT method. Besides, another conclusions could be obviously realized that the existence of a bit error rate would inevitably influence the whole image quality. In the empty pipe, with the BER ranging  
Figure 10: Waveform analysis of DIFRT (**a**) waveform of first relay node, (**b**) waveform of second relay node, and (**c**) waveform of final receiver (transmission rate=50 kbps).  
from 0.0037 to 0.0074, the PSNR and the SSIM value of the image were average 3.318 and 0.047 higher than the test value in the water pipe. That illustrated the water could in some degree reduce the transmission ability whether it was an analog signal or digital signal.  
Figure 11: The performance comparison between DIFRT and AISRT.