Robust Small Target Co-Detection from Airborne Infrared Image Sequences

Abstract

In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

Range Performance Modelling of Thermal Imaging System based on Single Parameter Characterised by Ambient Temperature and Relative Humidity

“…Night vision thermal and image processing performance model (NVTHERM-IP) developed by NVESD, US Army 17 have been used for acquisition range calculations. Comparative detection, recognition and identification range performance [19][20][21] for the two thermal imaging systems against a standard NATO target of size 2.3 m x 2.3 m with ∆T = 2 °C for clear atmosphere characterised by V=23 km and haze characterised by 5 km have been given as function of AH in Fig. 2 to 4.…”

An Omnidirectional Morphological Method for Aerial Point Target Detection Based on Infrared Dual-Band Model

“…According to the SNR of the to-be-detected point target, we assume that the SNR of the point target of IR Channel 1 (SNR 1 ) is 3 and that of IR Channel 2 (SNR 2 ) is 4. By iterating the TNR 1 of Channel 1 (from −3 to 4), we obtain the simulation curve of fused probability of detection via TNR 1 , as shown in Figure 2. The simulation result shows that the optimal fused probability of detection is 0.7931, which is higher than that of any single-band model.…”

“…When the aerial target is far away from the infrared focal plane array (IRFPA), the signal intensity is very weak, and the minutiae are very small. More seriously, the target image is easily obstructed by bad weather, atmospheric radiation, nonstationary cloud and random noise, which lead to a very low signal-to-noise ratio (SNR) in the image [4]. These difficulties call for additional requirements for the detection system and target detection algorithm.…”

Detection of Small Target Using Schatten 1/2 Quasi-Norm Regularization with Reweighted Sparse Enhancement in Complex Infrared Scenes

“…Along with the advance of infrared imaging technology, small target detection has been attracting great research interests in infrared search and tracking applications, such as precision guidance, defense early warning, and maritime target searching [1,2]. The efficient and robust performance of detection has an important role to play in these applications.…”

“…Representative single target images from the datasets and the separated target images obtained by six low-rank recovery-based methods (1)(2)(3)(4). are four representative single target images from the tested datasets.…”