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

Table 5

The PSNR and SSIM values of all denoising modes (NP of ASOMA, modified SOMA, HBSOMA, OSOMA, and SOMA is 50).

Denoising method		Salt and pepper		Gaussian		Additive
		PSNR	SSIM	PSNR	SSIM	PSNR	SSIM
Noisy image		58.8654	0.3685	56.8503	0.242	59.8716	0.477
Wavelet type	sym4	68.4766	0.8378	66.5357	0.7419	69.9310	0.9023
	sym6	68.5211	0.8395	66.555	0.7429	70.0367	0.9048
	sym8	68.5187	0.8394	66.5474	0.7432	69.9830	0.9036
	sym10	68.5302	0.8399	66.5365	0.7431	70.0540	0.9052
	db4	68.5000	0.8385	66.5249	0.7419	69.9444	0.9026
	db6	68.4745	0.8380	66.5609	0.7418	69.9950	0.9039
	db8	68.5373	0.8401	66.5428	0.7435	70.0420	0.9049
	coif2	68.5041	0.8387	66.5616	0.7423	69.9458	0.9027
	coif4	68.5317	0.8398	66.5461	0.7435	69.9958	0.9039
ASOMA		70.1460	0.8787	68.5699	0.8114	71.8587	0.9338
Modified SOMA		70.1460	0.8787	68.5699	0.8113	71.8587	0.9338
HBSOMA		70.1460	0.8787	68.5699	0.8113	71.8587	0.9338
OSOMA		70.1460	0.8787	68.5699	0.8114	71.8587	0.9338
SOMA		70.1460	0.8787	68.5698	0.8113	71.8585	0.9338