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Fast infrared dim and small target tracking

The target tracking by the spatio-temporal learning is a kind of online tracking algorithm based on Bayesian framework. But it has the excursion problem when applied in the infrared dim target. Based on the principle of the spatio-temporal learning algorithm, the excursion problem was analyzed and a new robust algorithm for infrared dim target tracking is proposed in this paper. Firstly, the Guide Image Filter was adopted to process the input image to preserve edges and eliminate the noise of the image. Secondly, the ideal spatial context model was calculated with the input image that contains little noise, which can be got by subtracting the filtering result from the original image. Simultaneously, a new weight in the context prior model was proposed to indicate that the prior is also related to the local gray level difference. The performance of the presented algorithm was tested with two infrared air image sequences, and the experimental results show that the proposed algorithm performs well in terms of efficiency, accuracy and robustness.