Region-based sub-pixel motion estimation from noisy, blurred, and down-sampled sequences

  • Authors:

  • Osama A. Omer;Toshihisa Tanaka

  • Affiliations:

  • Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan;Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan

  • Venue:
  • PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
  • Year:
  • 2006

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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.