An Image Denoising Method Based on BM4D and GAN in 3D Shearlet Domain

Table 3

The results of the different method for standard Gaussian white noise with .

PSNR; SSIM; EPI; Time/s	BM3D	EPLL	TNRD	WNNM	WSNM	Proposed
Cameraman	29.45	29.23	29.71	29.63	29.70	30.12
	0.70	0.70	0.74	0.71	0.75	0.76
	0.33	0.31	0.35	0.45	0.45	0.50
	0.54	31.43	0.92	261.72	289.96	4.57
Barbara	31.18	28.98	29.63	31.83	31.84	31.27
	0.75	0.71	0.75	0.77	0.82	0.85
	0.37	0.33	0.40	0.44	0.56	0.60
	3.14	179.30	1.64	1706.84	2350.22	10.62
Lena	30.60	30.30	30.77	30.88	30.89	32.27
	0.68	0.72	0.75	0.80	0.80	0.82
	0.32	0.36	0.40	0.46	0.47	0.48
	0.47	34.78	0.91	259.41	287.63	6.22
House	32.86	32.04	32.54	33.23	33.23	33.28
	0.66	0.76	0.80	0.83	0.80	0.83
	0.29	0.40	0.50	0.56	0.56	0.57
	1.49	31.16	0.92	263.04	298.06	6.43
Peppers	30.16	30.07	30.55	30.40	30.41	31.67
	0.64	0.77	0.81	0.81	0.82	0.80
	0.26	0.31	0.40	0.40	0.44	0.55
	0.44	32.25	0.87	259.73	291.05	4.88
Baboon	25.23	25.34	25.39	25.42	25.44	26.16
	0.62	0.71	0.77	0.77	0.78	0.80
	0.26	0.25	0.34	0.46	0.46	0.50
	1.62	106.28	1.23	986.96	1296.27	9.60