Local Spatial-Temporal Matching Method for Space-Based Infrared Aerial Target Detection.

Lue Chen,Peng Rao,Xin Chen,Maotong Huang

doi:10.3390/s22051707

Abstract

The feature of a space-based infrared signal is that the intensity of clutter is much stronger than that of an aerial target. Such a feature poses a great challenge to aerial target detection since the existing infrared target detection methods are prone to enhance clutter but ignore the real target, which results in missed detection and false alarms. To tackle the challenge, we propose a concise method based on local spatial–temporal matching (LSM). Specifically, LSM mainly consists of local normalization, local direction matching, spatial–temporal joint model, and inverse matching. Local normalization aims to enhance the target to the same strength as the clutter, so that the weak target will not be ignored. After normalization, a direction-matching step is applied to estimate the moving direction of the background between the basic frame and referenced frame. Then the spatial–temporal joint model is constructed to enhance the target and suppress strong clutter. Similarly, inverse matching is conducted to further enhance the target. Finally, a salience map is obtained, on which the aerial target is extracted by the adaptive threshold segmentation. Experiments conducted on four space-based infrared datasets indicate that LSM handles the above challenge and outperforms seven state-of-the-art methods in space-based infrared aerial target detection.

Highlights

The task of aerial target detection is of great importance in many fields, including air traffic surveillance [1] and intelligence reconnaissance [2]
To conquer the above challenge, we propose a space-based IR aerial target detection method based on local spatial–temporal matching (LSM), which has a concise structure
24.0300 where the aerial target is much weaker than clutter, as shown in images in Seqs.1, 2, and 4, spatial–temporal local contrast filter (STLCF), spatial–temporal local contrast method (STLCM), fusion saliency map (FSM), neighborhood saliency map (NSM), and double-neighborhood gradient method (DNGM) suppress most of the background in the images, It is worth noting that background suppression factor (BSF) is a global index evaluating the background suppression but the clutter with strong intensities is still retained

Summary

Introduction

The task of aerial target detection is of great importance in many fields, including air traffic surveillance [1] and intelligence reconnaissance [2]. Imaging technology has the advantages of all-day and wide-area imaging, while both the on-orbit experiment [3] and ground theoretical research [4] have certified that an aerial target can be detected by space-based IR detectors. Research on space-based IR aerial target detection continues to attract much attention. The sizes of the aerial targets on the space-based IR images range from 5 × 5 to 9 × 9 pixels, which is in accordance with the definition [5] of IR small target. Space-based IR aerial target detection is considerably different from ground-based IR small target detection. The complex earth background and frequent human activities generate strong clutter whose spatial characters are similar to the small target in space-based images

Methods

Results

Discussion

Conclusion