Infrared maritime target detection based on edge dilation segmentation and multiscale local saliency of image details

Abstract

Infrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. It is challenging to detect dark and weak targets and targets of different sizes. Some methods utilizing grayscale features unable to detect dark targets owing to the inconsideration of the target whose grayscale is lower than its local background. To solve this problem, the medium and high-frequency information in the image is extracted and used as the basis for feature extraction. Besides, although methods based on local contrast can solve the problem of missing detection caused by weak targets with obscure features, the local contrast calculation may be inaccurate and the targets may be missed when the size of the sliding window and target are unmatched. To solve this problem, an edge dilation segmentation method is proposed to obtain complete suspected targets. Then each suspected target is taken as the central block of the local area to ensure that both weak targets and targets of different sizes can be detected. In addition, some wave clutter is prone to cause false alarms due to its characteristics similar to the target. To solve this problem, the multiscale local backgrounds are constructed with certain proportions of the size of the suspected target, and the local saliency of the suspected target is calculated to separate the target from the clutters. Compared with the ten leading methods, the proposed method shows outstanding results, with relatively higher detection accuracy.