|
|
|
| Research on Infrared Image Object Detection Method Based on Deformable DETR |
| ZHANG Xiaoyu1， DU Xiangrun1， ZHANG Jialiang2，
TAN Panlong1， YANG Shibo1 |
| 1. College of Artificial Intelligence， Nankai University， Tianjin 300350， China；
2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109，China |
|
|
|
|
Abstract The DETR series networks based on the Transformer architecture keep pushing the boundaries of object detection accuracy and speed in computer vision. However, non-cooperative object detection applications based on infrared images face challenges because of environmental complexity and poor image quality. To solve this problem, a novel object detection algorithm with high detection accuracy was proposed in this study, utilizing the Deformable DETR as the baseline. Initially, an image enhancement module called CLAHE-GB was designed to enhance the image process on infrared images, and it was effectively integrated with Deformable DETR. Subsequently, the algorithm was pre-trained on a large-scale general dataset. Then, data augmentation and transfer learning methods were developed to retrain the parameters of the detection head network using a self-made dataset of small infrared images of aerial objects. Finally, a comprehensive result analysis was conducted. The results show that the proposed algorithm can successfully achieve promising image enhancement effects and detection accuracy on infrared image data.
|
|
Received: 18 October 2023
Published: 04 March 2024
|
|
|
|
|
|
| [1] |
CHEN Jichi, WEI Guohua, CHAI Juanfang . A Method for Evaluating the Effect and Accuracy of 3D Reconstruction Based on Infrared Image[J]. Air & Space Defense, 2023, 6(4): 42-50. |
| [2] |
WEI Zhifei, SONG Quanhong, LI Fang, YANG Qingyu, WANG Aihua. Research on Object Detection Algorithm Based on Neural Network Model Compression Technique[J]. Air & Space Defense, 2021, 4(4): 107-112. |
| [3] |
QIU Zhongyu, ZHAO Wenlong, GAO Wen, PAN Hongtao, SHI Randong. Comparison and Analysis of Object Detection Algorithm Based on Dynamic Vision Sensor[J]. Air & Space Defense, 2021, 4(4): 101-106. |
| [4] |
SHI Yuanbin, ZHANG Xiaojie, WANG Xing. Infrared Dual-Band Target Detection Method Based on Gradient and Anisotropic Diffusion[J]. Air & Space Defense, 2021, 4(4): 95-100. |
| [5] |
HU Jinhao, WANG Minghao, XIA Tianyang, WANG Yuexing, DU Haijing, XU Chuangang. Methods for Infrared-Visible Light Image Fusion Based on HSV Color Space[J]. Air & Space Defense, 2021, 4(4): 87-94. |
| [6] |
CAI Yunze, ZHANG Yanjun. Infrared Dim and Small Target Detection Based on Dual-Channel Feature-Enhancement Integrated Attention Network[J]. Air & Space Defense, 2021, 4(4): 14-22. |
| [7] |
JIANG Xinghao, ZHAO Zheyu, XU Ke . Adversarial Attack Technology for Vision-Based Aircraft Intelligent Object Detection[J]. Air & Space Defense, 2021, 4(1): 8-13. |
| [8] |
YU Xiaolong, XIAO Yongsheng, NIE Jianghua, MAO Cong. Infrared Image Line Detection Based on Improved Hough Transform[J]. Air & Space Defense, 2021, 4(1): 47-51. |
| [9] |
CHEN Jichi, WEI Guohua, GUO Conglong, ZHANG Lihe. Preliminary Study on a Deep Learning 3D Reconstruction Simulation Method Based on Infrared Image Sequence[J]. Air & Space Defense, 2020, 3(4): 21-29. |
|
|
|
|
2024, Vol. 7 
