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

Table 3

The PSNR and SSIM values of all denoising modes (NP of ASOMA, modified SOMA, HBSOMA, OSOMA, and SOMA is 10).

Denoising method		Salt and pepper		Gaussian		Additive
		PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
Noisy image		58.8396	0.3654	56.8839	0.2473	59.8627	0.4756
Wavelet type	sym4	68.4568	0.8361	66.6583	0.7516	69.9202	0.9018
	sym6	68.4142	0.8350	66.7123	0.7544	69.9959	0.9036
	sym8	68.4770	0.8369	66.6970	0.7536	69.9789	0.9032
	sym10	68.4384	0.8359	66.7168	0.7548	70.0153	0.9041
	db4	68.4551	0.8360	66.6781	0.7524	69.9350	0.9021
	db6	68.4229	0.8353	66.6620	0.7522	69.9595	0.9028
	db8	68.4054	0.8355	66.7270	0.7551	70.0166	0.9040
	coif2	68.4582	0.8361	66.6761	0.7524	69.9394	0.9022
	coif4	68.4741	0.8368	66.7081	0.7542	69.9901	0.9034
ASOMA		69.9664	0.8758	68.7435	0.8131	71.5814	0.9301
Modified SOMA		69.9661	0.8753	68.5508	0.8121	71.5776	0.9299
HBSOMA		69.9663	0.8756	68.5594	0.8116	71.5776	0.9299
OSOMA		69.9661	0.8752	68.5594	0.8127	71.5657	0.9300
SOMA		69.9657	0.8750	68.5532	0.8095	71.5657	0.9300