Adaptive wireless network multi-objective optimization algorithm based on image synthesis

Zhang, Jianwei; Zhang, Xueya

doi:10.1186/s13640-018-0289-3

EURASIP Journal on Image and Video Processing

Table 1 Quantification comparison between the method put forward in this paper and the multi-objective optimization algorithm

From: Adaptive wireless network multi-objective optimization algorithm based on image synthesis

Image	Algorithm	Threshold value	Threshold value Q	Between-class variance (Otsu)	Regional consistency	Misclassification rate	Time (s)
Lena that contains salt and pepper noise	Multi-objective optimization algorithm	205	0.7129	4690.0631	0.9840	0.0317	2.7708
	Exhaustive adaptive wireless network multi-objective optimization algorithm	205	0.5000	4690.0631	0.9844	0.0311	25.1347
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	205	0.5616	4690.0631	0.9844	0.0311	2.8872
Lena that contains Gaussian noise	Multi-objective optimization algorithm	209	0.7129	5209.0500	0.9601	0.0862	2.7887
	Exhaustive adaptive wireless network multi-objective optimization algorithm	209	0.5000	5209.0500	0.9674	0.0862	26.7024
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	209	0.5000	5209.0500	0.9674	0.0862	2.9927
Lena that contains mixed noise	Multi-objective optimization algorithm	210	0.7129	5126.5648	0.9531	0.1048	2.7829
	Exhaustive adaptive wireless network multi-objective optimization algorithm	201	0.5000	5126.5648	0.9617	0.0828	25.0975
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	210	0.5000	5126.5648	0.9617	0.0828	2.9424
Brodatz-Bark that contains salt and pepper noise	Multi-objective optimization algorithm	229	0.7129	4168.8897	0.9622	0.0661	2.7931
	Exhaustive adaptive wireless network multi-objective optimization algorithm	229	0.7500	4168.8897	0.9628	0.0645	26.0785
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	229	0.7852	4168.8897	0.9628	0.0645	2.9750
San Diego that contains Gaussian noise (Miramar NAS)	Multi-objective optimization algorithm	235	0.7129	5247.8310	0.9541	0.0922	2.8085
	Exhaustive adaptive wireless network multi-objective optimization algorithm	235	0.6250	5247.8310	0.9541	0.0922	25.5469
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	235	0.7101	5247.8310	0.9541	0.0922	2.9555
Chemical Plant, frame26 that contains mixed noise	Multi-objective optimization algorithm	189	0.7129	3659.8647	0.8619	0.0757	1.3513
	Exhaustive adaptive wireless network multi-objective optimization algorithm	189	0.6250	3659.8647	0.8619	0.0757	16.9575
	Adaptive wireless network multi-objective optimization algorithm put forward in this paper	189	0.6901	3659.8647	0.8619	0.0757	1.7279

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