计算机科学 ›› 2021, Vol. 48 ›› Issue (12): 231-242.doi: 10.11896/jsjkx.201000055
张育龙1, 王强1, 陈明康2, 孙静涛3
ZHANG Yu-long1, WANG Qiang1, CHEN Ming-kang2, SUN Jing-tao3
摘要： 《2020 年中国智能物联网(AIoT)白皮书》显示,随着我国5G网络的迅猛发展,大容量低价格的IoT(Internet of Things)传感器设备快速普及,数据呈爆发性增长,图像处理在物联网的诸多领域(如智慧城市、智慧交通、智慧医疗等)得到了广泛应用。在这些领域研究中,科研人员往往相对轻视数据收集过程中的实际问题,如天气变化、季节迁移、昼夜交替等时间变化带来的图像数据退化,以及随着物体移动、叠加、模糊、部分遮挡等诸多空间变化带来的噪声问题。其中,以雨天为代表的复杂天气下的图像模糊问题非常常见,也最具挑战。因此,文中对数据收集过程中的上述实际问题进行了系统性的调查,归类和总结了复杂天气下的图像去雨算法。与此同时,鉴于此类算法的执行需要消耗大量GPU计算资源,文中通过利用Amazon EC2云服务器中G4和P3系列的GPU实例对综述的各种去雨算法的处理时长和去雨效果进行了定量化评估,并阐述了各类去雨算法的特点和在云物联网应用中的最新趋势。
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