Temporal Profile Based Small Moving Target Detection Algorithm in Infrared Image Sequences

International Journal of Infrared and Millimeter Waves (Impact Factor: 0.67). 04/2007; 28(5):373-381. DOI: 10.1007/s10762-007-9214-z


A new algorithm is presented which deals with the problem of detecting small moving targets in infrared image sequences that
also contain drifting and evolving clutter. Through development of models of the temporal behavior of the static background,
target and cloud edge on a single pixel basis, the new algorithm employing the connecting line of the stagnation points (CLSP)
of the temporal profile as the baseline is created and tested. The deviation of the temporal profile and its CLSP is analyzed
and it is determined that the distribution of the residual temporal profile obtained by subtracting the baseline from the
temporal profile can be modeled by a Gaussian distribution. The occurrences of the targets have intensity values significantly
different to the distribution of the residual temporal profile. Unlike the conventional 3-D method, this new algorithm operates
on the temporal profile in 1-D space, not in 3-D space, thus having a higher computational efficiency. Experiments with real
IR image sequences have proved the validity of the new approach.

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    ABSTRACT: Track initiation for dim small moving target particularly in a heavy clutter environment is a theoretical and technological challenge for diverse tracking systems. The different spatial-temporal characteristics presenting in sequence scans are utilized to recognize target and initialize track in this paper. In spatial domain, the small target mapped in the image is a uniform gray spot other than pixel-sized object with high congregated degree, whereas, the false alarm is independent, irrelative and lower congregated degree. In temporal domain, the target’s trajectory projected on image sequence is continuous for the continuity of target motion and will appear in the neighborhood at consecutive instants with the maximum probability, on the contrary, the false alarm is disorderly, and occurs in the neighborhood at consecutive instants is impossible. Based on the spatial-temporal characteristics mentioned above, a track initiation algorithm for dim small moving target based on spatial-temporal hypothesis testing, which consists of neighborhood clustering and trajectory continuity, is derived and analyzed in detail. The theory analysis and experimental results show that this method could effectively initialize the track for dim small moving target in heavy clutter environment.
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    ABSTRACT: A new spatiotemporal target detection method that utilizes the recursive temporal profile (RTP) and the spatiotemporal gradient pattern (STGP) is proposed for infrared (IR) image sequence. In the IR search and tracking system, long-distance aerial targets compared with short-distance aerial targets appear to be composed of several pixels with no special shapes and their movements are slow. Considering the characteristics of aerial targets, an algorithm based on the STGP and fuzzy-set theory is proposed to detect long-distance aerial targets while the recursive temporal profile algorithm based on the temporal profile and mean estimation is proposed to detect short-distance aerial targets. In addition, the RTP and the STGP are combined to detect the aerial targets that exist at diverse distances in the IR image sequence. The performance of the proposed method is examined by using the receiver operating characteristic curve. The experiment results show that the proposed method performs better than the existing methods in terms of target detection and clutter removal.
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