# Reversible Data Hiding for DICOM Image Using Lifting and Companding
## 6 Performance Evaluation
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Wavelet Type**} & \multicolumn{8}{c}{**Images**} \\ \cline{2-7}  & **A** & **B** & **C** & **D** & **E** & **F** \\ \hline haar & \(83\times 10^{-7}\) & \(86\times 10^{-7}\) & \(81\times 10^{-7}\) & \(89\times 10^{-7}\) & \(87\times 10^{-7}\) & \(83\times 10^{-7}\) \\ db1 & \(48\times 10^{-7}\) & \(7\times 10^{-7}\) & \(80\times 10^{-7}\) & \(65\times 10^{-7}\) & \(93\times 10^{-7}\) & \(86\times 10^{-7}\) \\ sym2 & \(9\times 10^{-7}\) & \(1\times 10^{-6}\) & \(99\times 10^{-7}\) & \(27\times 10^{-7}\) & \(12\times 10^{-7}\) & \(3\times 10^{-6}\) \\ cdf1.1 & \(5\times 10^{-7}\) & \(47\times 10^{-6}\) & \(48\times 10^{-7}\) & \(17\times 10^{-7}\) & \(163\times 10^{-7}\) & \(23\times 10^{-7}\) \\ bior1.1 & \(15\times 10^{-7}\) & \(4\times 10^{-7}\) & \(38\times 10^{-4}\) & \(14\times 10^{-7}\) & \(1\times 10^{-10}\) & \(7\times 10^{-4}\) \\ rbiol.1 & \(24\times 10^{-7}\) & \(1\times 10^{-7}\) & \(71\times 10^{-7}\) & \(6\times 10^{-7}\) & \(2\times 10^{-10}\) & \(24\times 10^{-7}\) \\ bs3 & \(1\times 10^{-4}\) & \(6\times 10^{-4}\) & \(71\times 10^{-7}\) & \(15\times 10^{-8}\) & \(1\times 10^{-10}\) & \(39 DICOM frames are then averaged. Transmission of watermarked DICOM frames through Rayleigh fading channel followed by the averaging operation is one way of implementing collusion operation. In the mobile radio communication system, the low value of SNR suggests that the channel is under deep fade. On the other hand, the high value of SNR represents the opposite. In the present scenario, high and low SNR values represent light and heavy collusion operations, respectively [29]. We also test the anti-collusion performance of the proposed scheme by directly averaging watermarked DICOM frame, but without channel fading. This operation is called a non-fading based collusion operation. Figure 10 shows a few frames from 'Lung' DICOM image database. Figure 11a shows a watermarked frame after non-fading based collusion operation. Figure 11b-f show watermarked DICOM frames after time-varying collusion attacks with different SNR (transmitting each watermarked DICOM frames through fading channel at different SNR values) and then averaged. Table 5 shows the BER (bit error rate) values for different watermarks extracted from the colluded average images. Low BER values indicate that the scheme is robust to fading like collusion operation. It is also seen that the BER values for _columns_ 2-5 are quite low compared to the BER values in _column_ 6. The low values of BER clearly indicate that the parties having watermarks, i.e., W\({}_{1}\), W\({}_{2}\), W\({}_{3}\), W\({}_{4}\), are identified as colluders. It is also quite clear from the numerical values of BER that parties involved in collusion operation would unambiguously be identified from the innocent users (W\({}_{5}\)). Similar results are also obtained if different combinations of watermarked  
The collusion performance of the proposed method is also compared with previously reported works [18; 19; 20; 38; 39] to demonstrate the performance comparison. In the time of comparison of our system with the previously proposed ones, we have used reference implementations provided by the authors. It is observed from the results of Figure 12 that the proposed method offers better gain in term of NCC than the others. This is because the present scheme uses the content dependent watermark to resist the collusion attack. As expected, in Figure 12, we have seen that as the number of frames being combined increases, the NCC value decreases. It is also seen that there is a dip in the curve for [38] in Figure 12. This is due to the fact that in their experimentation, every 5 thframe was extracted to form the actual set of test frames. So for every 5 thframe, there is a valley in the graph. The evaluation performance of the proposed reversible watermarking scheme is compared with the existing related works. Figure 13 shows the comparative performance in term of embedding capacity (in bpp) versus distortion in PSNR (dB).