Speckle Noise Removal by Energy Models with New Regularization Setting

Table 2

The PSNR of the restored images by the different model.

Image		ROF (PSNR/SSIM)	ATV (PSNR/SSIM)	JIN’s (PSNR/SSIM)	HYPTV (PSNR/SSIM)	LOGTV (PSNR/SSIM)
Peppers	2	27.60/0.7183	28.66/0.8377	29.46/0.8195	29.43/0.8250	29.53/0.8274
Boat	2	27.26/0.8240	27.90/0.8574	28.35/0.8622	28.49/0.8659	28.64/0.8661
House	2	27.45/0.6185	29.06/0.8101	28.77/0.6876	29.55/0.7374	29.74/0.7447
Pirate	2	28.33/0.8975	27.22/0.8530	28.51/0.9042	28.55/0.9047	28.74/0.9060
Bird	2	28.99/0.6907	30.28/0.7849	30.36/0.7774	30.88/0.8137	31.07/0.8173
Peppers	3	25.93/0.6758	26.70/0.7409	27.13/0.7446	27.19/0.7492	27.37/0.7516
Boat	3	25.79/0.7481	26.47/0.7986	26.68/0.8029	26.64/0.7985	26.82/0.7989
House	3	26.08/0.5752	27.33/0.6611	27.24/0.6551	27.62/0.6866	27.82/0.6896
Pirate	3	26.35/0.8392	26.38/0.8332	26.81/0.8578	26.85/0.8580	26.98/0.8583
Bird	3	27.36/0.6451	27.92/0.6930	28.48/0.7307	28.92/0.7686	29.13/0.7701
Peppers	4	24.49/0.6153	25.59/0.7153	25.63/0.6800	25.65/0.6981	25.83/0.7011
Boat	4	24.47/0.6807	24.95/0.7338	25.24/0.7370	25.31/0.7382	25.51/0.7388
House	4	24.63/0.5130	25.30/0.5760	26.18/0.6399	26.19/0.6419	26.43/0.6437
Pirate	4	24.03/0.7652	24.33/0.7205	24.75/0.7787	25.64/0.8118	25.77/0.8159
Bird	4	25.66/0.5679	26.49/0.6584	27.25/0.7263	27.25/0.7270	27.51/0.7282

Best denoising performance are given in bold.