Abstract
In recent years, a digital video stabilization improving the results of hand-held shooting or shooting from mobile platforms is the most popular approach. In this chapter, the task of digital video stabilization in static scenes is investigated. The unwanted motion caused by camera jitters or vibrations ought to be separated from the objects motion in a scene. Our contribution connects with the development of deblurring method to find and improve the blurred frames, which have strong negative influence on the following processing results. The use of fuzzy Takagi-Sugeno-Kang model for detection the best local and global motion vectors is the novelty of our approach. The quality of test videos stabilization was estimated by Peak Signal to Noise Ratio (PSNR) and Interframe Transformation Fidelity (ITF) metrics. Experimental data confirmed that the ITF average estimations increase up on 3–4 dB or 15–20 % relative to the original video sequences.
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