摘要
针对近海、内河场景中船只检测准确性低的问题,提出了一种基于短波红外遥感影像实现水体分割和船只自动检测的方法。利用水体在短波红外波段反射率低的特点,采取阈值分割和形态学处理的方法,从影像中快速准确地提取水体区域;使用视觉显著模型搜索水面目标,提取候选目标的图像切片;对可能存在的伪目标,使用灰度分布直方图描述目标切片的灰度分布特征,并结合梯度方向信息通过阈值判别的方法去除伪目标。结果表明,该方法能高效检测近海、内河中不同尺寸的船只目标;显著性检测共获得279个候选目标,经目标鉴别步骤检测出142个真实目标中的138个,虚警率小于6%,召回率大于97%。
Aiming at the problem of the ship detection with a low accuracy in the offshore and inland river scenes,a method based on shortwave infrared multispectral remote sensing images is proposed to realize water segmentation and automatic detection of ship.Based on the low reflectance characteristic of water area in the shortwave infrared frequency range,the water area is rapidly and accurately extracted from the images by using the threshold segmentation and morphological processing.Then,the image chips of candidate targets are extracted by using the visual saliency model for searching the targets in the water areas.As for the possible existence of phony targets,the gray-scale distribution histogram is proposed to describe the characteristics of gray-scale distribution of the target chips,which are combined with the gradient direction information to eliminate phony targets by the method of threshold constraint.The results show that the proposed method can efficiently detect the ship targets with different sizes in offshore and inland rivers.279 candidate targets are obtained after the saliency detection and 138 of 142 true targets are detected after the target discrimination step.The false discovery rate is less than 6% and the recall rate is higher than 97%.
引文
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