Object Detection by Deep Sparse Feature Learning of Salient Polarization Parameters

Meirong Wang; Guoming Xu; Hongwu Yuan

doi:10.3788/LOP56.191101

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 19 >Page 191101 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 19, 191101 (2019)

Object Detection by Deep Sparse Feature Learning of Salient Polarization Parameters

Meirong Wang¹, Guoming Xu^1、2、*, and Hongwu Yuan^1、2

Author Affiliations

¹Institute of Information Engineering, Anhui Xinhua University, Hefei, Anhui 230088, China

²Anhui Province Key Laboratory of Polarized Imaging Detecting Technology, Army Artillery and Air Defense Forces Academy, Chinese People's Liberation Army, Hefei, Anhui 230031, China

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DOI: 10.3788/LOP56.191101 Cite this Article Set citation alerts

Meirong Wang, Guoming Xu, Hongwu Yuan. Object Detection by Deep Sparse Feature Learning of Salient Polarization Parameters[J]. Laser & Optoelectronics Progress, 2019, 56(19): 191101 Copy Citation Text

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Fig. 1. Object detection framework

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Fig. 2. Object detection algorithm for salient polarization parameter image

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Fig. 3. Test data (0° polarization direction). (a) Airplane; (b) tank; (c) truck

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Fig. 4. Results of salient parameter image selection. (a1)-(c1) Images of airplane 1, airplane 2, and truck; (a2)-(c2) salient selected results

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Fig. 5. Results of object detection. (a1)-(c1) Images of airplane 1, airplane 2, and truck; (a2)-(c2) salient image detection results

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Criteria	Airplane 1		Airplane 2		Truck
Criteria	0°	Salient	0°	Salient	0°	Salient
E_n	3.75	6.84	5.29	6.54	6.22	6.77
$\begin{matrix} \bar{g} \end{matrix}$	0.31	0.29	0.36	0.39	0.87	0.61
σ	5.55	29.94	30.22	25.65	75.69	44.19

Table 1. Results before and after polarization analysis and salient parameter image selection

Object	mAP	AP
Object	mAP	Airplane 1	Airplane 2	Tank 1	Truck	Tank 2
Polarization angle of 0°	63.88	69.3	61.2	71.4	66.4	51.1
Polarization angle of 60°	63.08	68.5	59.8	70.6	65.9	50.6
Polarization angle of 120°	63.42	69.0	60.3	70.8	66.3	50.7
I	63.72	70.2	60.1	72.3	65.8	50.2
Q	60.64	64.4	57.4	68.8	61.3	51.3
U	53.7	64.9	37.6	62.9	54.4	48.7
P	60.46	70.3	45.3	70.1	67.1	49.5
A	52.24	59.4	37.7	58.8	60.7	44.6
E_x	61.18	70.0	57.6	67.0	63.5	47.8
E_y	59.56	64.7	56.8	56.2	67.9	52.2
ΔE	57.74	64.6	53.6	55.3	65.4	49.8
β	31.85	N	N	N	23.4	40.3

Table 2. Comparison of detection results of different image objects

Model	Time /s	mAP/average	Airplane 1	Airplane 2	Tank
Model	Time /s	mAP/average	AP/score	AP/score	AP/score
Faster R-CNN	0.7	66.1/0.741	68.1/0.842	59.5/0.619	70.6/0.762
Proposed	24	67.9/0.819	70.3/0.897	61.2/0.680	72.3/0.881

Table 3. Comparison of detection results of different models

Meirong Wang, Guoming Xu, Hongwu Yuan. Object Detection by Deep Sparse Feature Learning of Salient Polarization Parameters[J]. Laser & Optoelectronics Progress, 2019, 56(19): 191101

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