# Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability
## 1 Introduction  
IR imaging based small moving target detection is one of the most significant techniques for military, astronautics and aeronautics applications [1]. The performance of an infrared search and track (IRST) system highly relies on the precision of small target detection. A high-performance IR small target detection algorithm should remove the background clutters effectively and examine the real targets not only in a single frame, but also in consecutive frames. Moreover, motion trajectories need to be delineated, which makes it easier to monitor and capture the targets of interest. Although modern IR detectors possess the advantages of fast detection, cheap equipment and simple setup [2], the specific imaging mechanism and detection condition still result in the following inherent properties of IR images which cause much inconvenience for target detection [3; 4; 5]. On the one hand, IR imaging is based on IR radiation, so the target/background contrast may be weak if their radiometric quantities are similar. Furthermore, it is an inevitable fact that pixel size of the existing IR cameras cannot be small enough to generate high-resolution images, which means the images to be processed are alwaysblurred. In addition, the target size becomes comparatively small (fewer than 20 \(\times\) 20 pixels) on account of the long military observation distance. To efficiently examine small moving targets and remove various sorts of background clutters in IR images simultaneously, numerous algorithms have been developed so far, including filter based methods, mathematical morphology based methods, wavelet based methods, and so on. Filter based methods, the representatives of which are max-mean/max-median filter [6], high-pass filter [7] as well as two-dimensional least mean square (TDLMS) filter [8], utilize fixed templates to suppress clutters according to intensity difference. Although they can meet the requirement of real-time processing, the results are always inaccurate [9; 10]. Mathematical morphology theory, like Hat transformation (including top-hat and bottom-hat transformation) [11], is another embranchment in the field of small target detection. These kinds of methods are aimed at enhancing regions of interest via morphological operations, but usually fails when the target is dim or the clutter is heavy [12; 13]. Wavelet based algorithms [14] design a group of filters which are matched to a point spread function (PSF) at different scales by choosing a mother wavelet similar to PSF. Unfortunately, they are quite time-consuming and the false alarm rates are always high [15]. Although much progress has been achieved in the past decades, there are some significant problems that remain to be worthy of further investigation: on the one hand, dark target whose IR radiation is lower than the surroundings is seldom covered in previous algorithms; furthermore, using motion features to eliminate false alarms created in the single frame and forming complete trajectories are still tough tasks. In this paper, we first present a new saliency histogram on the basis of a saliency map to distinguish visually salient regions from the background. Based on the fact that both bright and dark IR small targets have relatively different grayness with the background, proving IR small targets can be seen as salient regions in IR images, the gray levels correspond to targets would be assigned with large bin values in the saliency histogram. Then, an adaptive threshold is calculated via [PERSON]'s method [16; 17; 18] to roughly extract IR targets according to the above-constructed histogram, and sub-pixel-accuracy centroid coordinates of all of the candidate target regions are obtained through a connected components labeling algorithm and an intensity-weighted criterion. For consecutive frames, we apply a uniformly accelerated motion model to make track correlations [19] and form completed motion trails for each candidate point.