Improved Gradient Threshold Image Sharpness Evaluation Algorithm

Haifei Zeng; Changpei Han; Kai Li; Huangwei Tu

doi:10.3788/LOP202158.2211001

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 22 >Page 2211001 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 22, 2211001 (2021)

Improved Gradient Threshold Image Sharpness Evaluation Algorithm

Haifei Zeng^1、2、3, Changpei Han^1、2、*, Kai Li^1、2、3, and Huangwei Tu^1、2、3

Author Affiliations

¹Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China

²Key Laboratory of Infrared Detection and Imaging Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China

³University of Chinese Academy of Sciences, Beijing 100049, China

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DOI: 10.3788/LOP202158.2211001 Cite this Article Set citation alerts

Haifei Zeng, Changpei Han, Kai Li, Huangwei Tu. Improved Gradient Threshold Image Sharpness Evaluation Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2211001 Copy Citation Text

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Fig. 1. Sample image 1. (a) 1^st frame image; (b) focusing image; (c) 25^th frame image

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Fig. 2. Sample image 2. (a) 1^st frame image; (b) focusing image; (c) 17^th frame image

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Fig. 3. Sample image 3. (a) 1^st frame image; (b) focusing image; (c) 24^th frame image

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Fig. 4. Normalized sharpness evaluation curves of different images. (a) Sample image 1; (b) sample image 2; (c) sample image 3

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Fig. 5. Normalized sharpness evaluation curves of different noised images. (a) Sample image 1 after adding Gaussian noise; (b) sample image 1 after adding salt and pepper noise; (c) sample image 2 after adding Gaussian noise; (d) sample image 2 after adding salt and pepper noise; (e) sample image 3 after adding Gaussian noise; (f) sample image 3 after adding salt and pepper noise

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Type of image	Brenner	Roberts	Roberts-energy	SMD	EOG	SML	Sobel	Proposed algorithm
Sample image 1	32.48	27.20	27.46	26.52	37.05	43.38	46.96	25.18
Sample image 2	32.37	27.20	27.37	26.39	36.48	42.65	46.72	25.23
Sample image 3	32.24	27.20	27.39	26.45	36.61	42.96	47.22	25.29

Table 1. Time delay required by different sharpness evaluation algorithms to process a frame of image unit: ms

Type of image	Index
Sample image 1	f_sen	0.539	0.387	0.584	0.389	0.585	0.650	0.318	0.688
Sample image 1	S	0.316	0.238	0.325	0.238	0.321	0.333	0.203	0.345
Sample image 2	f_sen	0.885	0.810	0.873	0.818	0.868	0.854	0.783	0.912
Sample image 2	S	0.432	0.380	0.428	0.385	0.426	0.423	0.364	0.447
Sample image 3	f_sen	0.776	0.596	0.800	0.613	0.814	0.863	0.540	0.789
Sample image 3	S	0.393	0.302	0.402	0.309	0.409	0.431	0.272	0.398

Table 2. Sensitivity index of different algorithms

Image type	Noise type	Noise parameter	Brenner	Roberts	RbtEnergy	SMD	EOG	SML	Sobel	Proposed algorithm
Sample image 1	Gaussiannoise	0.01	1.230	1.060	1.170	1.030	1.100	1.050	1.130	6.630
		0.02	1.110	1.030	1.080	1.020	1.050	1.030	1.080	7.520
		0.05	1.040	1.020	1.030	1.020	1.030	1.030	1.030	9.790
	Salt & peppernoise	0.05	1.200	1.290	1.150	1.200	1.100	1.080	1.220	6.600
		0.10	1.100	1.140	1.080	1.090	1.060	1.050	1.120	7.560
		0.20	1.070	1.060	1.050	1.040	1.040	1.030	1.050	9.870
Sample image 2	Gaussiannoise	0.01	1.647	1.191	1.490	1.110	1.280	1.130	1.406	18.330
		0.02	1.313	1.096	1.230	1.050	1.120	1.050	1.260	21.720
		0.05	1.100	1.029	1.069	1.020	1.040	1.050	1.110	30.510
	Salt & peppernoise	0.05	1.510	1.970	1.410	1.700	1.270	1.190	1.930	18.410
		0.10	1.270	1.460	1.220	1.330	1.160	1.120	1.420	22.580
		0.20	1.150	1.200	1.130	1.140	1.100	1.090	1.170	30.720
Sample image 3	Gaussiannoise	0.01	1.224	1.073	1.166	1.035	1.077	1.057	1.191	70.299
		0.02	1.057	1.027	1.040	1.344	1.049	1.066	1.070	96.661
		0.05	1.038	1.017	1.026	1.023	1.023	1.031	1.044	111.138
	Salt & peppernoise	0.05	1.139	1.044	1.099	1.032	1.051	1.065	1.133	78.777
		0.10	1.049	1.023	1.033	1.030	1.036	1.051	1.059	101.441
		0.20	1.025	1.010	1.018	1.013	1.008	1.011	1.027	122.629

Table 3. Sharpness ratio of different sharpness evaluation algorithms in different noise environments

Haifei Zeng, Changpei Han, Kai Li, Huangwei Tu. Improved Gradient Threshold Image Sharpness Evaluation Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2211001

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