Abstract
The blind pixel suppression is the key preprocess to guarantee the real-time space-based infrared point target (IRPT) detection and tracking. Meanwhile, flickering pixels, as one of the blind pixels, is hard to suppress because of randomness. At present, common methods adopting a single feature generally need to accumulate dozens or hundreds of frames to ensure detection accuracy, which cannot update flickering pixels frequently. However, with low detection frequency, the flickering pixels are easily miss detected. In this paper, we propose an on-board flickering pixel dynamic suppression method based on multi-feature fusion. The visual and motion features of flickering pixels are extracted from the result of IRPT detection and tracking. Then, the confidence of flickering pixel evaluation strategy and selection mechanism of flickering pixel are introduced to fuse the above features, which achieves accurate flickering pixel suppression using a dozen frames. The experimental results evaluated on the real image of four scenarios show that the blind pixel false detection rate of the proposed method is no more than 1.02%. Meanwhile, evaluated on the simulated image, the flickering pixel miss suppression rate is no more than 2.38%, and the flickering pixel false suppression rate is 0. The proposed method could be an addition to most other IRPT detection methods, which guarantees the near-real-time and reliability of on-board IRPT detection applications.
Highlights
Space-based infrared point target (IRPT) detection is one of the most important applications of the on-board intelligent information processing technology, which has been wildly used in both the civil and military fields
From the above results and analysis, we propose a visual feature extraction method based on the facet model using the result of IRPT detection as input to distinguish blind based on the facet model using the result of IRPT detection as input to distinguish blind pixels from suspected IRPT
According to the experimental data and evaluation criterion above, the proposed method is compared with the scene-based bad pixel dynamic correction (SBBPDC) method [13] and the calibration-based adaptive threshold bad pixel detection (CBATBPD) method [9]
Summary
Space-based infrared point target (IRPT) detection is one of the most important applications of the on-board intelligent information processing technology, which has been wildly used in both the civil and military fields. Threshold filter [1], coding mechanism [2], and support vector machine [3], etc., are proposed to eliminate false alarm sources and have obtained good results in the IRPT detection algorithm. These sophisticated methods consume most computing resources to eliminate more indistinguishable false alarm sources from background. These blind pixels have a catastrophic effect on on-board intelligent information processing if they are not properly suppressed
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