Table 2.

Performance analysis of our algorithm. For each level of noise we performed 100 independent runs of the algorithm, corresponding to different independent realizations of noise and beaming directions. The table reports the mean and standard deviation (over 100 runs) of the RMSE for denoising using PCA with the asymptotically optimal linear filter, the optimal parameter values α and β, and the ${\ell }_1$ norm of the wavelet expansion of the reconstructed image.

SNR [dB]	RMSE	α	β	${\ell }_1$
10	0.350 ± 0.001	7.1 ± 2.5	0.41 ± 0.02	228.9 ± 1.3
5	0.417 ± 0.001	5.2 ± 1.1	0.41 ± 0.02	256.3 ± 1.6
3	0.448 ± 0.001	5.1 ± 0.9	0.44 ± 0.05	266.7 ± 8.4
2	0.464 ± 0.002	5.3 ± 1.0	0.45 ± 0.05	270.4 ± 9.4
1	0.478 ± 0.002	5.3 ± 0.9	0.44 ± 0.05	271.1 ± 8.8
0	0.497 ± 0.002	5.6 ± 1.0	0.44 ± 0.04	271.4 ± 7.7
–1	0.514 ± 0.002	6.0 ± 1.1	0.45 ± 0.05	273.6 ± 8.4
–2	0.532 ± 0.002	6.4 ± 1.4	0.45 ± 0.05	273.1 ± 6.1
–3	0.550 ± 0.002	6.4 ± 1.6	0.45 ± 0.05	275.3 ± 7.1
–4	0.568 ± 0.002	6.3 ± 1.8	0.47 ± 0.06	284.3 ± 8.8
–5	0.588 ± 0.002	7.5 ± 2.1	0.53 ± 0.06	292.0 ± 0.2