Abstract

Satellite videos dynamically monitor the Earth’s surface by using staring imaging, which has gained increased attention and enabled target tracking applications. While various tracking methods are processed on the original video, the rapid light changes due to staring imaging are not considered and have a negative effect on tracking. To reduce the effects of illumination and improve the performance of satellite video target tracking, an intrinsic satellite video decomposition model with motion target energy constraint, called MTE-ISVD, is proposed in this paper. The proposed algorithm introduces two main constraints: The first is a temporal constraint of reflectance, which can solve the flicker problem by preserving reflectance coherence in the time domain with the property that the background pixels in satellite videos are nearly consistent between adjacent frames. The second is a motion target energy constraint, which can concentrate the signal energy of the motion targets in the reflectance by representing them with the surrounding background in the shading. The decomposition problem is reformulated as a quadratic function minimization, which can be addressed using the standard conjugate gradient in closed form. For visual and quantitative comparisons, we perform experiments on five Jilin-1 satellite videos and analyze the results in terms of visual comparison, target tracking improvement, stability evaluation and processing time comparison. The experimental results demonstrate that our proposed method outperforms the other representative intrinsic decomposition methods in terms of processing speed, stability, and motion target representation.

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