22 May 2012 Simultaneous spatial-temporal image fusion using Kalman filtered compressed sensing
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Abstract
Image fusion is a process to combine multiple frames of the same scene into one image. The popular image fusion methods mainly concentrate on static image fusion and lack spatial-temporal adaptability. The conventional multi-resolution image fusion algorithms have not fully exploited the temporal information. To resolve this problem, we present a novel dynamic image fusion algorithm based on Kalman filtered compressed sensing. The fusion procedure characterized by estimation fusion is completed in state space. A parametric fusion model is proposed to learn and combine spatial and temporal information simultaneously. The experiments on the ground-truth data sets show that the proposed fusion algorithm offers a considerable improvement on the dynamic fusion performance and rivals the traditional multi-resolution-based fusion methods.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Han Pan, Zhongliang Jing, Rongli Liu, Bo Jin, "Simultaneous spatial-temporal image fusion using Kalman filtered compressed sensing," Optical Engineering 51(5), 057005 (22 May 2012). https://doi.org/10.1117/1.OE.51.5.057005 . Submission:
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