An Adaptive Self-Organizing Migration Algorithm for Parameter Optimization of Wavelet Transformation

Table 4

The PSNR and SSIM values of all denoising modes (NP of ASOMA, modified-SOMA, HBSOMA, OSOMA, and SOMA is 30).

Denoising method		Salt and pepper		Gaussian		Additive
		PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
Noisy image		58.8511	0.3668	56.8652	0.2429	59.8627	0.4754
Wavelet type	sym4	68.4152	0.8354	66.5297	0.7419	69.9202	0.9011
	sym6	68.4584	0.8371	66.5775	0.7446	69.9019	0.9015
	sym8	68.4631	0.8372	66.5486	0.7431	69.9388	0.9022
	sym10	68.4727	0.8377	66.5807	0.7449	69.9256	0.9021
	db4	68.4386	0.8361	66.5379	0.7422	69.9026	0.9012
	db6	68.4449	0.8367	66.5442	0.7432	69.8639	0.9006
	db8	68.4869	0.8380	66.5807	0.7447	69.9355	0.9022
	coif2	68.4341	0.8360	66.5389	0.7423	69.9164	0.9015
	coif4	68.4729	0.8375	66.5546	0.7433	69.9479	0.9024
ASOMA		69.9733	0.8756	68.5879	0.8209	71.6292	0.9322
Modified SOMA		69.9723	0.8754	68.5818	0.8184	71.6213	0.9314
HBSOMA		69.9728	0.8755	68.5798	0.8184	71.6278	0.9320
OSOMA		69.9720	0.8754	68.5873	0.8180	71.6276	0.9320
SOMA		69.9706	0.8750	68.3868	0.8180	71.6104	0.9313