Adaptive Top-Hat Infrared Small Target Detection Based on Local Contrast

Tengyan Xi; Lihua Yuan; Shupeng Wang

doi:10.3788/LOP222850

Laser & Optoelectronics Progress, Volume. 60, Issue 16, 1628003(2023)

Adaptive Top-Hat Infrared Small Target Detection Based on Local Contrast

Tengyan Xi¹, Lihua Yuan^1、*, and Shupeng Wang²

¹Key Laboratory of Nondestructive Testing, Ministry of Education, College of Testing and Optoelectronic Engineering, Nanchang Hangkong University, Nanchang 330063, Jiangxi, China

²China Aviation Development Shenyang Liming Aero Engine Co., Ltd., Shenyang 110000, Liaoning, China

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Figures & Tables(20)

Fig. 1. Schematic of target area

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Fig. 2. Original image and LCM map. (a) Original image; (b) LCM map

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Fig. 3. Schematic of structural elements

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Fig. 4. Schematic of size setting of structural elements

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Fig. 5. Overall process of ATHLC method

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Fig. 6. Schematic of target area

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Fig. 7. Simulation results of three backgrounds at each stage

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Fig. 8. Experimental results of similar methods. (a) Original images; (b) 3D gray scale images of original image; (c) Top-Hat; (d) NWTH; (e) PITH; (f) ATHLC

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Fig. 9. Comparison diagrams of different classes of methods. (a) Original images; (b) ADMD; (c) AADCCD; (d) HBMLCM; (e) RLCM; (f) MPCM; (g) PSTNN; (h) ATHLC

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Fig. 10. Three dimensional gray scale representation of different classes of methods. (a) Original images; (b) ADMD; (c) AADCCD; (d) HBMLCM; (e) RLCM; (f) MPCM; (g) PSTNN; (h) ATHLC

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Fig. 11. ROC curves of different methods

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Fig. 12. PR curves of different methods

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Table 1. Sequence image information

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Table 1. Sequence image information

Sequence No.	Target size	Number of frames	Image size	Average SCR	Image description
Seq1	5 $\times$ 5	30	256 $\times$ 200	0.62	The cloud background，mostly covered by scattered clouds，has a fixed perspective and small targets from left to right.
Seq2	3 $\times$ 3	30	256 $\times$ 256	0.36	The complex ground background，mostly covered by vegetation and mountains，has a sloping dividing line from the moving perspective.
Seq3	3 $\times$ 3	30	256 $\times$ 256	1.46	Complex ground background，partially covered by mountain forest and ground，moving perspective.
Seq4	3 $\times$ 3	30	640 $\times$ 512	0.91	River and building background，the bridge span from top left to bottom right，with a fixed perspective，and the target are from top left to bottom right.
Seq5	1 $\times$ 1	30	640 $\times$ 512	1.08	Sky and architectural background，fixed perspective，target from right to left.
Seq6	3 $\times$ 3	30	640 $\times$ 512	0.26	The sky background，mostly covered by clouds，has a fixed viewing angle and targets from right to left.

Table 2. Parameter settings of comparison methods

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Table 2. Parameter settings of comparison methods

Method	Parameter setting
Top-Hat	Structuring type is disk；structuring element size is 5×5
NWTH	R_o=9，R_i=4 for sequences 1-3；R_o=7，R_i=3 for sequences 4-6
PITH	B_o=9，B_i=4，B_e=3 for sequences 1-3；B_o=7，B_i=3，B_e=2 for sequences 4-6
ATHLC	B_o=11，B_i=5，Be=4 for sequences 1-3；B_o=9，B_i=4，B_e=3 for sequences 4-6；scale is 3，5；window size is 3×3；k'=4

Table 3. SCRG, BSF, and CG of similar methods

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Table 3. SCRG, BSF, and CG of similar methods

Sequence No.	Top-Hat SCRG/BSF/CG	NWTH SCRG/BSF/CG	PITH SCRG/BSF/CG	ATHLC SCRG/BSF/CG
Seq1	15.66/1.08/8.53	Inf/10.00/4.83	Inf/11.78/4.59	Inf/Inf/16.24
Seq2	16.04/0.88/9.12	345.99/5.66/9.01	434.45/6.76/8.90	Inf/Inf/29.73
Seq3	3.60/1.23/2.32	23.97/10.83/1.97	27.45/12.25/1.95	Inf/Inf/6.78
Seq4	4.16/1.57/1.70	Inf/31.79/1.87	Inf/34.45/1.87	Inf/300.58/9.90
Seq5	5.31/2.99/3.59	Inf/50.40/3.59	Inf/55.09/3.60	Inf/1550.09/19.79
Seq6	179.92/9.46/52.28	Inf/134.77/40.12	Inf/149.33/40.26	Inf/310.57/573.06

Table 4. Parameter settings for different classes of methods

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Table 4. Parameter settings for different classes of methods

Method	Parameter setting
ADMD	Scale is 3，5，7，9；window size is 3 $\times$ 3
AADCDD	Scale is 3，5，7，9；window size is 3 $\times$ 3
HBMLCM	Scale is 3，5，7，9；window size is 15 $\times$ 15
RLCM	Scale is 3； $k_{1}$ =2，5，9； $k_{2}$ =4，9，16
MPCM	Scale is 3，5，7，9；mean filtering size is 3 $\times$ 3
PSTNN	Patch size is 40 $\times$ 40；sliding step is 40； $λ = \frac{1}{\sqrt[]{m a x (m, n)}}$
ATHLC	B_o=11，B_i=5，B_e=4 for sequences 1-3；B_o=9，B_i=4，B_e=3 for sequences 4-6；scale is 3，5；window size is 3 $\times$ 3；k′=4

Table 5. SCRG of different classes of methods

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Table 5. SCRG of different classes of methods

Method	Seq1	Seq2	Seq3	Seq4	Seq5	Seq6
ADMD	224.59	Inf	30.71	Inf	Inf	3816.40
AADCDD	255.53	Inf	59.11	Inf	Inf	Inf
HBMLCM	89.14	120.94	29.66	49.78	82.70	1384.73
RLCM	112.66	48.78	27.98	120.97	Inf	Inf
MPCM	3.35	1.15	1.28	0.17	1.14	34.28
PSTNN	Inf	Inf	Inf	Inf	Inf	Inf
ATHLC	Inf	Inf	Inf	Inf	Inf	Inf

Table 6. BSF of different classes of methods

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Table 6. BSF of different classes of methods

Method	Seq1	Seq2	Seq3	Seq4	Seq5	Seq6
ADMD	15.16	4.53	5.02	13.23	22.03	28.93
AADCDD	9.55	4.91	4.82	7.30	26.88	116.93
HBMLCM	24.31	3.18	3.41	8.15	13.36	107.05
RLCM	4.08	1.73	4.78	7.06	12.78	25.71
MPCM	2.10	3.26	4.04	4.21	18.17	8.07
PSTNN	Inf	4.08	3.35	15.02	33.92	130.54
ATHLC	Inf	Inf	Inf	300.58	1550.09	310.57

Table 7. CG of different classes of methods

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Table 7. CG of different classes of methods

Method	Seq1	Seq2	Seq3	Seq4	Seq5	Seq6
ADMD	2.63	3.12	2.39	0.67	2.99	182.73
AADCDD	3.71	1.88	1.20	0.19	0.88	36.62
HBMLCM	3.82	5.51	2.62	0.77	2.83	317.84
RLCM	17.86	26.84	9.28	9.60	18.37	231.67
MPCM	2.30	0.67	0.94	0.30	0.78	34.86
PSTNN	6.21	6.43	1.89	1.49	3.07	45.57
ATHLC	16.24	29.73	6.78	9.90	19.79	573.06

Table 8. Running time of different classes of methods

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Table 8. Running time of different classes of methods

Method	Seq1	Seq2	Seq3	Seq4	Seq5	Seq6
ADMD	0.0253	0.0152	0.0130	0.0380	0.0370	0.0358
AADCDD	0.0260	0.0271	0.0265	0.0939	0.0940	0.0923
HBMLCM	0.0153	0.0147	0.0131	0.0543	0.0556	0.0470
RLCM	0.9791	1.3668	1.3906	7.1697	7.5835	6.7185
MPCM	0.0335	0.0423	0.0446	0.1742	0.1789	0.1779
PSTNN	0.0423	0.1697	0.1883	0.9150	0.7672	0.5253
ATHLC	0.0242	0.0367	0.0327	0.1331	0.1335	0.1289

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Tengyan Xi, Lihua Yuan, Shupeng Wang. Adaptive Top-Hat Infrared Small Target Detection Based on Local Contrast[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1628003

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Paper Information

Category: Remote Sensing and Sensors

Received: Oct. 20, 2022

Accepted: Nov. 25, 2022

Published Online: Aug. 18, 2023

The Author Email: Yuan Lihua (lihuayuan@nchu.edu.cn)

DOI:10.3788/LOP222850

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology