Ship wake extraction and detection from infrared remote sensing images

In infrared remote sensing images with low or medium spatial resolution, the number of pixels occupied by ships on the sea is very small, and the geometric shape and specific texture structure of the target are difficult to obtain. In order to improve the detection limit signal to clutter ratio, the ship wake feature with linear feature was taken as the detection element, which was mathematically characterized. The Dot-Curve detection system was established innovatively. Based on the two-dimensional curvature filtering, the ship detection and wake feature extraction were carried out preliminarily. The feature set was established, from which a number of features with large difference from the background interference items, including wake gray variance, positive and negative gray slope on both sides of the wake, wake linearity and the distance from the hull detection results, were selected to identify the detection results of the candidate targets, remove interference items and extract targets. The results show that after target identification, the ship false detection rate in different bands of infrared images is reduced to less than 8.40%, and the detection rate is improved to at least 94.53%. The ship detection algorithm combines the physical and image characteristics of the wake, which is suitable for many scenes and bands. The algorithm is refined and effective, the physical laws are clear, and the samples needed are few.