红外海面小目标检测算法综述

Review of Infrared Sea Surface Small-target Detection Algorithm

红外成像技术是一种无源探测技术,已广泛运用于陆海空天等各个领域,具有强大的抗干扰能力和目标测量全天候等优点。红外成像跟踪测量系统已在海面飞行器参数测量中大量应用。红外海面小目标检测技术是处理红外测量图像的重要环节,合适的检测方法能够提高判读结果的准确度和效率。通过分析红外海面小目标图像中背景、目标的特性及红外海面小目标复杂识别技术难题,对比了基于深度学习和基于传统方法的两种红外小目标算法,阐述了传统算法的原理、步骤及优势,并分析了红外小目标检测算法的未来发展趋势。

Infrared imaging technology is a passive detection technology that has been widely used in various fields such as land,sea,air and space,with the advantages of strong resistance to external interference and all-weather target measurement.Infrared imaging tracking and measurement systems have been used in a large number of applications in the measurement of surface vehicle parameters. Infrared sea surface small-target detection technology is an important part of processing infrared measurement images.The accuracy and efficiency of the interpretation results can be improved with suitable detection methods. By analyzing the characteristics of the background and target in the infrared sea surface small target image and the technical difficulties of the complex recognition of infrared sea surface small-targets,two infrared small-target algorithms based on deep learning and traditional methods are compared. The principle,steps and advantages of the traditional algorithms are elaborated,and the future development trend of infrared small-target detection algorithms is analyzed.