This work describes an automatic detection method of obstacles covered by snow. The method is based on the detection of statistical anomalies relative to an estimated background image which contains no obstacles. The sensitivity of the detection can be adjusted by a specified probability of false alarms, and the obstacle detection confidence is characterized by a probability of detection. Statistical properties of the background image are estimated from the given image without additional information on the background. The visible height of obstacles above the snow is related to the actual height of the obstacles above the ground, so that an operator can estimate the actual height of the snow covered obstacle. The developed method requires no training, is self-calibrating to the cluttered images, operates with a single given image, and aligns with a detection quantification adopted in the receiver operating characteristic framework.

这项工作描述了一种自动检测被雪覆盖的障碍物的方法。该方法基于检测相对于不包含障碍物的估计背景图像的统计异常。检测的灵敏度可以通过指定的误报概率进行调整，障碍物检测置信度由检测概率来表征。背景图像的统计特性是根据给定图像估计的，没有关于背景的附加信息。雪上障碍物的可见高度与障碍物实际的离地高度有关，便于操作者估计雪覆盖障碍物的实际高度。开发的方法不需要训练，可以对杂乱的图像进行自我校准，对单个给定图像进行操作，