Abstract
Digital image stabilization (DIS) becomes one of the most important features in consumer cameras. The image sequence is easily interfered by hand-shaking during acquisition process especially in zoom-in highly. Many of the state-of-the-art algorithms for image stabilization perform well for high patterned and clear images. However, for high noise or low pattern level images, the algorithm performance degrades seriously. In this paper, we propose a novel digital image stabilization algorithm for removal of unwanted motion in high noise or low pattern level images. The proposed algorithm consists of an adaptive Kalman filter for motion prediction and a binary edge transform (BET) based phase correlation (PC) for motion estimation. Since the proposed algorithm is designed for real-time implementation, it can be used as an algorithm for a DIS to preserve a good environment that the photograph has been taken of many commercial applications such as low cost camcorders, digital cameras, CCTV, and surveillance video systems.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kwon, O., Nam, B., Paik, J. (2006). Binary Edge Based Adaptive Motion Correction for Accurate and Robust Digital Image Stabilization. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_115
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DOI: https://doi.org/10.1007/11949534_115
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
Online ISBN: 978-3-540-68298-1
eBook Packages: Computer ScienceComputer Science (R0)