Abstract
Motion estimation is one of the most important steps in super-resolution algorithms for a video sequence, which require estimating motion from a noisy, blurred, and down-sampled sequence; therefore the motion estimation has to be robust. In this paper, we propose a robust sub-pixel motion estimation algorithm based on region matching. Non-rectangular regions are first extracted by using a so-called watershed transform. For each region, the best matching region in a previous frame is found to get the integer-pixel motion vector. Then in order to refine the accuracy of the estimated motion vector, we search the eight sub-pixels around the estimated motion vector for a sub-pixel motion vector. Performance of our proposed algorithm is compared with the well known full search with both integer-pixel and sup-pixel accuracy. Also it is compared with the integer-pixel region matching algorithm for several noisy video sequences with various noise variances. The results show that our proposed algorithm is the most suitable for noisy, blurred, and down-sampled sequences among these conventional algorithms.
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© 2006 Springer-Verlag Berlin Heidelberg
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Omer, O.A., Tanaka, T. (2006). Region-Based Sub-pixel Motion Estimation from Noisy, Blurred, and Down-Sampled Sequences. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_27
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DOI: https://doi.org/10.1007/11922162_27
Publisher Name: Springer, Berlin, Heidelberg
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