南方电网技术2024，Vol.18Issue(6)：138-147,10.DOI:10.13648/j.cnki.issn1674-0629.2024.06.016
基于逐像素自适应对抗网络的电力巡检图像增强方法
Electric Power Patrol Inspection Image Enhancement Method with Per-Pixel Self-Paced Adversarial Network
摘要
Abstract
In view of the problem that the image details are lost and the edges are blurred in the intelligent patrol inspection of electric power,resulting in the wrong target detection and recognition,a super-resolution method based on per-pixel selt-paced adversarial network(PSPA)is proposed.This method is based on the generation of adversarial network,adds multiple attention mechanisms,and restores the detailed texture through pixel by pixel comparison.The experimental results show that the super-resolution images generated by this method are not only superior to the existing algorithms in human visual system,but also 6.2 and 0.099 3 times higher than the existing algorithms in PSRN and SSIM.Then Yolov3 is applied on the super-resolution images recovered by different algorithms in the UAV transmission line insulator dataset and the power construction helmet wearing dataset.The experimental results demonstrate that the proposed method could not only decreases the residual error rate,but also improves the detection confidence as high as the high-resolution images关键词
电力巡检图像增强/生成对抗网络/逐像素自适应/多重注意力机制Key words
electric power patrol inspection image enhancement/generative adversarial network/per-pixel self-paced/multiple attention mechanism分类
信息技术与安全科学引用本文复制引用
庄雪澄,邵洁..基于逐像素自适应对抗网络的电力巡检图像增强方法[J].南方电网技术,2024,18(6):138-147,10.基金项目
国家自然科学基金资助项目(61802250) （61802250）
上海市科委地方院校能力建设项目(20020500700). Supported by the National Natural Science Foundation of China(61802250) （20020500700）
the Local College Capacity Building Project of Shanghai Municipal Commission of Science and Technology(20020500700). （20020500700）
