This paper proposes a digital video stabilization algorithm based on block motion estimation and iterative optimization of global motion parameters (GMP). In the algorithm, a block matching algorithm based on rotation invariant feature is used to estimate the local true motion vectors of the center of all the blocks considered. Using these local motion vectors and their corresponding block positions, a linear system is constructed, and the GMPs are generated by solving them by repeated least squares method. Then, an iterative optimization algorithm is used to improve the overall motion parameters. The experimental results show that, compared with the ever presented digital image stabilization based on circular block matching technique, it can produce more accurate GMP and output more clear and stable image sequences.
The intent of video stabilization to remove violent jitter in the video and reduce video distortion. Recently, many excellent video stabilization algorithms have been proposed. However, it is a question to assess the video stabilization performance objectively. In order to solve the problem, we propose a novel objective assessment method for video stabilization performance by computing the distance, distortion and similarity between the stabilized and reference frames. According to published video stabilization database, data sets are built and tested. Finally, the experimental results demonstrate the accuracy of our proposed assessment method and the results are consistent with subjective human eyes.
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