## 5 Experimental Results
### PSNR Comparisons
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Block Size** & \multicolumn{2}{c}{**2 × 2**} & \multicolumn{2}{c}{**1 × 3**} \\ \hline  & [16] & **Proposed Method** & [17] & **Proposed Method** \\ \hline Bell & 34.39 & 41.45 & 37.51 & 41.13 \\ Bricks & 36.00 & 35.44 & 34.97 & 36.95 \\ Church & 36.21 & 42.07 & 38.06 & 41.29 \\ Cliffs & 33.28 & 39.51 & 36.05 & 39.50 \\ Kangaroo & 36.53 & 40.31 & 32.63 & 39.99 \\ Kinkaku-ji Temple & 34.60 & 38.61 & 34.66 & 38.54 \\ Monkeys & 36.08 & 39.53 & 34.87 & 39.99 \\ Mosque & 37.42 & 40.38 & 38.70 & 40.03 \\ Painting & 35.94 & 41.79 & 37.58 & 41.47 \\ Rice paddies & 36.18 & 41.18 & 36.46 & 40.93 \\ Statue & 30.79 & 39.28 & 35.25 & 38.77 \\ Sydney Opera & 40.18 & 43.87 & 39.07 & 43.80 \\ House & Temple & 40.22 & 40.38 & 36.39 & 40.51 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: PSNRs of [PERSON] et al.’s [16], [PERSON] et al.’s [17], and the proposed methods with a capacity 45,000 bits and \(k=3\). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Capacity (Bits)** & \multicolumn{2}{c}{**15,000, \(k=1\)**} & \multicolumn{2}{c}{**30,000, \(k=2\)**} \\ \hline  & [16] & **Proposed Method** & [16] & **Proposed Method** \\ \hline Aerial & 38.78 & 41.99 & 36.71 & 39.31 \\ Airplane & 46.29 & 47.18 & 42.95 & 44.09 \\ Balloon & 45.10 & 48.04 & 42.14 & 44.14 \\ Earth & 43.70 & 50.61 & 42.45 & 47.22 \\ Girl & 42.57 & 43.33 & 39.40 & 40.12 \\ Lena & 41.51 & 45.21 & 39.17 & 41.89 \\ Parrots & 40.22 & 42.22 & 37.05 & 38.54 \\ Pepper & 41.42 & 42.53 & 38.02 & 39.17 \\ Mandrill & 38.82 & 40.34 & 35.81 & 37.30 \\ Couple & 41.44 & 46.16 & 39.77 & 43.18 \\ Sailboat & 40.62 & 43.96 & 38.24 & 40.76 \\ Milkdrop & 45.61 & 47.47 & 42.09 & 43.35 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Peak signal-to-noise ratios (PSNRs) of [PERSON] et al.’s [16] and the proposed methods. Figure 3: Results of [PERSON] et al.’s palette reordering for Lena. Figure 2: Results of [PERSON] et al.’s parity assignment with \(k=1\) for Lena. In the second experiment, we compared the proposed method with the methods proposed by [PERSON] et al. [16] and [PERSON] et al. [17] with a capacity of 45,000 bits and \(k=3\). Note that for the image Couple, only 43,845 bits can be embedded using [PERSON] et al. 's method. Part of results is listed in Table 4, which reveals that the proposed method provides the best image quality under the same capacity. The reason is the same as that in experiment 1. Furthermore, our method modifies at most one pixel during data embedding; other methods [16; 17] may modify more than one pixel during data embedding. As mentioned previously, [PERSON] et al. and [PERSON] et al. 's methods need an extra location map to record which blocks are used for embedding, in experiment 3, the location map is embedded into a stego image. According to Table 2, the maximum valid embedding capacity of [PERSON] et al. and [PERSON] et al. 's methods are \(12,288\times k\) and \(16384\times k\), respectively. Table 5 shows part of image qualities of [PERSON] et al. 's, [PERSON] et al. 's, and our methods under the same embedding capacity. Note that to enforce embedding the location map in the first 4096 (5467) blocks for [PERSON] et al. 's ([PERSON] et al. 's) method, all indices 0 (255) of pixels in these blocks are changed to 1 (254) before embedding; this will avoid overflow/underflow after embedding. From these tables, we can see that image qualities of the proposed method are always superior to those of [PERSON] et al. and [PERSON] et al. 's methods under the same embedding capacity. The main reason is that embedding the location map will occupy several blocks and reduce the embedding capacity. Thus, under the same embedding capacity, those blocks used for embedding the location map in [PERSON] et al. and [PERSON] et al. 's methods will be skipped for data embedding in the proposed method. This will make the proposed method have higher image quality.