Object Detection Algorithm of Optical Remote Sensing Images Based on YOLOv3

Category	Training set	Verification set	Test set
Airplane	344	338	705
Airport	326	327	657
Baseball field	551	577	1312
Basketball court	336	329	704
Bridge	379	495	1304
Chimney	202	204	448
Dam	238	246	502
Expressway service area	279	281	565
Expressway toll station	285	299	634
Golf course	216	239	491
Ground track field	536	454	1322
Harbor	328	332	814
Overpass	410	510	1099
Ship	650	652	1400
Stadium	289	292	619
storage tank	391	384	839
Tennis court	605	630	1347
Train station	244	249	501
Vehicle	1556	1558	3306
Wind mill	404	403	809
Total	5862	5863	11738

Table 2. Numbers of images in training set, verification set, and test set of each category
View table
Table 2. Numbers of images in training set, verification set, and test set of each category
Category Training set Verification set Test set
Playground 37 34 78
Overpass 44 44 88
Oiltank 41 41 83
Aircraft 111 112 223
Total 233 231 472

Table 3. Numbers of images in training set, verification set, and test set of each category
View table
Table 3. Numbers of images in training set, verification set, and test set of each category
Category Training set Verification set Test set
Airplane 75 75 150
Ship 50 50 100
Total 125 125 250

Table 4. Test results of different models on DIOR dataset

View table

Table 4. Test results of different models on DIOR dataset

Parameter		SSD(300×300)^[15]	SSD(512×512)^[15]	Faster RCNN^[1]	YOLOv3^[5]	Ours
AP /%	Airplane	49.1	59.5	53.6	72.2	75.9
	Airport	62.1	72.7	49.3	29.2	39.3
	Baseball field	66.2	72.4	78.8	74.0	77.8
	Basketball court	72.0	75.7	66.2	78.6	82.7
	Bridge	26.1	29.7	28.0	31.2	38.6
	Chimney	63.3	65.8	70.9	69.7	72.7
	Dam	54.0	56.6	62.3	26.9	34.9
	Expressway service area	62.7	63.5	69.0	48.6	53.7
	Expressway toll station	46.6	53.1	55.2	54.4	58.5
	Golf course	64.8	65.3	68.0	31.1	40.8
	Ground track field	53.1	68.6	56.9	61.1	64.2
	Harbor	44.2	49.4	50.2	44.9	48.3
	Overpass	34.7	48.1	50.1	49.7	59.7
	Ship	44.4	59.2	27.7	87.4	91.7
	Stadium	58.3	61.0	73.0	70.6	74.9
	Storage tank	42.1	46.6	39.8	68.7	73.2
	Tennis court	72.6	76.3	75.2	87.3	90.9
	Train station	37.4	55.1	38.6	29.4	36.7
	Vehicle	22.7	27.4	23.6	48.3	54.8
	Wind mill	47.1	65.7	45.4	78.7	81.9
mAP /%		51.2	58.6	54.1	57.1	62.6
Time /s		0.021	0.032	0.180	0.024	0.042

Table 5. Test results of different models on RSOD dataset

View table

Table 5. Test results of different models on RSOD dataset

Parameter		SSD(300×300)^[15]	SSD(512×512)^[15]	Faster RCNN^[1]	YOLOv3^[5]	Ours
AP /%	Aircraft	68.0	86.1	76.2	89.7	91.6
	Oiltank	90.5	90.6	94.3	90.5	92.6
	Playground	90.3	90.4	96.0	90.2	91.8
	Overpass	77.3	73.3	69.1	63.3	68.7
mAP /%		81.5	85.1	83.9	83.4	86.2
Time /s		0.021	0.034	0.180	0.024	0.042

Table 6. Test results of different models on partial TGRS-HRRSD dataset
View table
Table 6. Test results of different models on partial TGRS-HRRSD dataset
Parameter SSD(300×300) ^[15] SSD(512×512)^[15] Faster RCNN^[1] YOLOv3^[5] Ours
AP /% Ship 85.0 85.3 80.3 86.1 92.1
Airplane 87.4 89.9 94.1 90.0 92.5
mAP /% 86.2 87.6 87.2 88.0 92.3
Time /s 0.024 0.034 0.183 0.026 0.040

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Peng Wang, Xuejing Xin, Liqin Wang, Rui Liu. Object Detection Algorithm of Optical Remote Sensing Images Based on YOLOv3[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2028006

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Paper Information

Category: Remote Sensing and Sensors

Received: Nov. 11, 2020

Accepted: Jan. 20, 2021

Published Online: Oct. 15, 2021

The Author Email: Peng Wang (wangpeng1027@126.com), Xuejing Xin (1306014217@qq.com)

DOI:10.3788/LOP202158.2028006

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Numbers of images in training set, verification set, and test set of each category

Table 1. Numbers of images in training set, verification set, and test set of each category

Table 2. Numbers of images in training set, verification set, and test set of each category

Table 2. Numbers of images in training set, verification set, and test set of each category

Table 3. Numbers of images in training set, verification set, and test set of each category

Table 3. Numbers of images in training set, verification set, and test set of each category

Table 4. Test results of different models on DIOR dataset

Table 4. Test results of different models on DIOR dataset

Table 5. Test results of different models on RSOD dataset

Table 5. Test results of different models on RSOD dataset

Table 6. Test results of different models on partial TGRS-HRRSD dataset

Table 6. Test results of different models on partial TGRS-HRRSD dataset