# Reversible Data Hiding for DICOM Image Using Lifting and Companding
## 6 Performance Evaluation
However, till the KLD value is very low and approaching to zero (0). That ensures that the scheme is secured. The performance of different lifting based wavelets on the test images is shown in Table 2. It is seen that 'haar', 'db1' and 'bior1.1' offers better performance than the other wavelets. On the other hand, the performance of various wavelets and their image security value for a fixed payload of 65,536 bits is shown in Table 3. It is seen that in all test cases, the KLD values are very less and approaching to zero (0). That ensures that the scheme is secured for all type of lifting based wavelets. Table 4 shows the variation of PSNR, MSSIM for different payload size (for Lung image), and wavelets. It is seen that 'Haar', 'db1' and 'bior1.1' offers better performance than the others wavelets even if the payload is increased to 65,536 bits. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Images** & **Payload (in Bits)** & **2500** & **10,000** & **40,000** & **62,500** & **65,536** \\ \hline \multirow{3}{*}{Lung} & PSNR (dB) & 71.42 & 65.31 & 59.33 & 57.40 & 57.17 \\  & MSSIM & 1 & 0.9998 & 0.9997 & 0.9996 & 0.9995 \\  & KLD & \(4\times 10^{-7}\) & \(27\times 10^{-7}\) & \(69\times 10^{-7}\) & \(80\times 10^{-7}\) & \(83\times 10^{-7}\) \\ \hline \multirow{3}{*}{MRI-1} & PSNR (dB) & 71.33 & 65.42 & 59.29 & 57.37 & 57.15 \\  & MSSIM & 0.9999 & 0.9995 & 0.9989 & 0.9983 & 0.9982 \\  & KLD & \(14\times 10^{-7}\) & \(37\times 10^{-7}\) & \(60\times 10^{-7}\) & \(83\times 10^{-7}\) & \(86\times 10^{-7}\) \\ \hline \multirow{3}{*}{MRI-2} & PSNR (dB) & 71.23 & 65.38 & 59.33 & 57.35 & 57.16 \\  & MSSIM & 1 & 1 & 1 & 1 & 1 \\  & KLD & \(3\times 10^{-7}\) & \(25\times 10^{-7}\) & \(49\times 10^{-7}\) & \(78\times 10^{-7}\) & \(81\times 10^{-7}\) \\ \hline \multirow{3}{*}{Chest} & PSNR (dB) & 71.35 & 65.22 & 59.28 & 57.36 & 57.17 \\  & MSSIM & 1 & 0.9999 & 0.9995 & 0.9993 & 0.9992 \\  & KLD & \(12\times 10^{-7}\) & \(30\times 10^{-7}\) & \(52\times 10^{-7}\) & \(84\times 10^{-7}\) & \(89\times 10^{-7}\) \\ \hline \multirow{3}{*}{Ankle} & PSNR (dB) & 71.42 & 65.29 & 59.31 & 57.37 & 57.15 \\  & MSSIM & 1 & 0.9999 & 0.9994 & 0.9989 & 0.9989 \\  & KLD & \(9\times 10^{-7}\) & \(28\times 10^{-7}\) & \(49\times 10^{-7}\) & \(79\times 10^{-7}\) & \(87\times 10^{-7}\) \\ \hline \multirow{3}{*}{Retina} & PSNR (dB) & 71.31 & 65.36 & 59.33 & 57.38 & 57.15 \\  & MSSIM & 0.9999 & 0.9997 & 0.991 & 0.9985 & 0.9983 \\  & KLD & \(11\times 10^{-7}\) & \(25\times 10^{-7}\) & \(65\times 10^{-7}\) & \(81\times 10^{-7}\) & \(83\times 10^{-7}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Variation of PSNR (dB), MSSIM and KLD values for different payload size using lifting based ‘Haar’ wavelets. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Wavelet**} & \multicolumn{8}{c}{**Images**} \\ \cline{2-11}  & \multicolumn{2}{c}{**A**} & \multicolumn{2}{c}{**B**} & \multicolumn{2}{c}{**C**} & \multicolumn{2}{c}{**D**} & \multicolumn{2}{c}{**E**} & \multicolumn{2}{c}{**F**} \\ \cline{2-11}  & **M** & **P** & **M** & **P** & **M** & **P** & **M** & **P** & **M** & **P** \\ \hline haar & 0.9995 & 57.17 & 0.9982 & 57.15 & 1 & 57.16 & 0.9992 & 57.17 & 0.9989 & 57.15 & 0.9983 & 57.15 \\ db1 & 0.9950 & 57.14 & 0.9982 & 57.17 & 1 & 57.14 & 0.9942 & 57.12 & 0.9989 & 57.15 & 0.9983 & 57.14 \\ sym2 & 0.9994 & 54.54 & 0.9978 & 55.05 & 1 To study the performance for collusion operation, we simulate fading like operation on watermarked DICOM image. We call this operation as a fading based collusion operation. Commonly, when collusion attack occurs on a continuous multimedia signal such as audio, video and DICOM images, the evaluation of time-varying weights (TVW) become vital which is equivalent to different gains in fading channels. Fading in communication channel means random deviation in received signal strength. This occurs as multiple copies of the same message signal are received over variable path lengths [35; 36].