27 May 2016 Digital image stabilization in mountain areas using complete ensemble empirical mode decomposition with adaptive noise and structural similarity
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Abstract
Cameras mounted on scouting vehicles frequently suffer from image shake because of unintentional motions. Image shake is a main source of inaccuracies that lead to bad scouting results, particularly in mountain areas with complicated terrains. To overcome this disadvantage, this study proposes a digital image stabilization method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and structural similarity (SSIM) to generate a stable scouting video sequence. The proposed method first calculates the global motion vector (GMV) from a scouting video sequence using the bit-plane matching algorithm. To separate jitter motion from intentional motion, we decompose GMV into several modes using CEEMDAN. Then according to different structural characteristics, SSIM is used to draw a boundary among modes to separate jitter motion from intentional motion. To evaluate stabilization performance in complicated situations, several known methods and the proposed stabilization method are compared. Experimental results show that CEEMDAN outperforms the other stabilization methods under mountain area conditions.
© 2016 SPIE and IS&T
Duo Hao, Qiuming Li, Chengwei Li, "Digital image stabilization in mountain areas using complete ensemble empirical mode decomposition with adaptive noise and structural similarity," Journal of Electronic Imaging 25(3), 033007 (27 May 2016). https://doi.org/10.1117/1.JEI.25.3.033007 . Submission:
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