Abstract
Abstract Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel DVS algorithm that compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. The adaptive fuzzy filter is a simple infinite impulse response filter which is tuned by a fuzzy system adaptively to the camera motion characteristics. The fuzzy system is also tuned during operation according to the amount of camera jitters. The fuzzy system uses two inputs which are quantitative representations of the unwanted and the intentional camera movements. The global motion of video frames is estimated based on the block motion vectors which resulted by video encoder during motion estimation operation. Experimental results indicate a good performance for the proposed algorithm.
Highlights
Digital video stabilization (DVS) techniques have been studied for decades to improve visual quality of image sequences captured by compact and lightweight digital video cameras
Such local motion vectors (LMVs) are applicable to the local motion compensation task which is executed in the encoder, they cannot be used for the global motion compensation which is executed by the DVS
Since some of the obtained motion vectors (MVs) are not valid, an adaptive thresholding was developed to filter out valid MVs and to compute an accurate global motion vector (GMV) for each frame
Summary
Digital video stabilization (DVS) techniques have been studied for decades to improve visual quality of image sequences captured by compact and lightweight digital video cameras. Another approach, the global ME is limited to small, predefined regions [16,17] Such approaches consider DVS and video encoding separately and attempt to trade the accuracy of motion vectors (MVs) for the computational efficiency; they improve the computational efficiency at the expense of degradation in the accuracy in ME and thereafter in MC tasks. In video frames with smooth or complex texture regions, the estimated BMVs may not be in coincidence with the real motion of the blocks Such LMVs are applicable to the local motion compensation task which is executed in the encoder, they cannot be used for the global motion compensation which is executed by the DVS.
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