# Improved Image Denoising Algorithm Based on Superpixel Clustering and Sparse Representation
## 4 Experimental Results
### Quantitative Comparisons
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multicolumn{5}{c}{**(b) \(\delta=15\)**} \\ \cline{2-6}  & **NLM** & **KSVD** & **BM3D** & **EPLL** & **SC-SR** \\ \hline \multirow{3}{*}{**Baboon**} & 25.95 & 28.42 & 28.67 & 28.70 & **28.77** \\  & 0.6800 & 0.8227 & 0.8327 & **0.8421** & 0.8388 \\  & 0.7051 & 0.8234 & **0.8187** & 0.8117 & 0.7995 \\ \hline \multirow{3}{*}{**Fingerprint**} & 27.67 & 30.06 & 30.29 & 29.82 & **30.41** \\  & 0.8935 & 0.9462 & 0.9495 & 0.9462 & **0.9510** \\  & 0.6968 & 0.7075 & 0.7760 & 0.7761 & **0.7946** \\ \hline \multirow{3}{*}{**Airplane**} & 31.31 & 33.60 & 33.89 & 33.78 & **33.97** \\  & 0.8756 & 0.9100 & 0.9162 & **0.9163** & **0.9163** \\  & 0.7677 & 0.8095 & 0.8240 & **0.8540** & 0.8482 \\ \hline \multirow{3}{*}{**Monarch**} & 29.73 & 31.45 & 31.97 & 32.06 & **32.10** \\  & 0.8999 & 0.9282 & 0.9384 & 0.9379 & **0.9407** \\  & 0.9016 & 0.9226 & 0.9281 & **0.9397** & 0.9386 \\ \hline \multirow{3}{*}{**Lena**} & 31.45 & 33.73 & **34.25** & 33.84 & 34.12 \\  & 0.8454 & 0.8860 & **0.8953** & 0.8893 & 0.8928 \\  & 0.6457 & 0.7552 & 0.7920 & **0.8185** & 0.8093 \\ \hline \multirow{3}{*}{**House**} & 32.64 & 34.34 & 34.96 & 34.12 & **35.02** \\  & 0.8561 & 0.8778 & 0.8901 & 0.8768 & **0.8922** \\  & 0.7430 & 0.8541 & **0.8878** & 0.8749 & 0.8769 \\ \hline \multirow{3}{*}{**Peppers**} & 30.23 & 32.25 & **32.69** & 32.55 & 32.64 \\  & 0.8624 & 0.8998 & **0.9064** & 0.9054 & 0.9050 \\  & 0.8123 & 0.8260 & 0.8408 & **0.8869** & 0.8661 \\ \hline \multirow{3}{*}{**Straw**} & 26.67 & 28.57 & 28.65 & 28.53 & **28.72** \\  & 0.8661 & 0.9270 & 0.9291 & 0.9281 & **0.9350** \\  & 0.6833 & 0.7960 & 0.8049 & **0.8060** & 0.7952 \\ \hline \multirow{3}{*}{**Hill**} & 28.89 & 31.45 & 31.85 & 31.69 & **31.88** \\  & 0.7270 & 0.8227 & 0.8394 & 0.8382 & **0.8428** \\  & 0.5812 & 0.7682 & 0.7800 & **0.8013** & 0.7959 \\ \hline \multirow{3}{*}{**Woman**} & 29.91 & 31.92 & **32.42** & 32.23 & 32.38 \\  & 0.7860 & 0.8433 & **0.8545** & 0.8537 & 0.8543 \\  & 0.6355 & 0.7834 & 0.8018 & **0.8363** & 0.8323 \\ \hline \multirow{3}{*}{**Average**} & 29.45 & 31.58 & 31.96 & 31.73 & **32.00** \\  & 0.8292 & 0.8864 & 0.8952 & 0.8934 & **0.8969** \\  & 0.7172 & 0.8046 & 0.8254 & **0.8405** & 0.8357 \\ \hline \multirow{3}{*}{**Images**} & \multicolumn{5}{c}{**(c) \(\delta=25\)**} \\ \cline{2-6}  & **NLM** & **KSVD** & **BM3D** & **EPLL** & **SC-SR** \\ \hline \multirow{3}{*}{**Baboon**} & 22.85 & 25.79 & 26.04 & **26.18** & 26.13 \\  & 0.4955 & 0.7081 & 0.7300 & **0.7483** & 0.7300 \\  & 0.4036 & 0.7245 & 0.7174 & 0.7245 & **0.7403** \\ \hline \multirow{3}{*}{**Fingerprint**} & 24.32 & 27.30 & 27.72 & 27.14 & **27.79** \\  & 0.7979 & 0.8984 & **0.9117** & 0.9050 & **0.9117** \\  & 0.5974 & 0.6371 & 0.7034 & 0.6772 & **0.7321** \\ \hline \multirow{3}{*}{**Airplane**} & 28.17 & 30.97 & 31.44 & 31.27 & **31.45** \\  & 0.8286 & 0.8719 & 0.8833 & 0.8794 & **0.8865** \\  & 0.6036 & 0.7306 & 0.7419 & **0.7904** & 0.7638 \\ \hline \multirow{3}{*}{**Monarch**} & 26.43 & 28.72 & 29.31 & 29.33 & **29.44** \\  & 0.8336 & 0.8880 & 0.9031 & 0.9001 & **0.9045** \\  & 0.8066 & 0.8532 & 0.8821 & 0.9024 & **0.9076** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: \(Cont.\)