An effective algorithm of electronic image stabilization （EIS） of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows：① A model of electronic im...An effective algorithm of electronic image stabilization （EIS） of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows：① A model of electronic image stabilization is built by analyzing the imaging theory and the principle of EIS, and the image shift function of unwrapped panoramic image is deduced;② The relationship equation between motion estimation parameters of annular panoramic image and motion estimation parameters of unwrapped panoramic image is developed according to the constrained aspect ratio of real objects, motion parameters of annular panoramic image are firstly estimated, and then motion parameters among the image shift function are carried out according to the relationship equation;③ An excessive stabilization threshold is presented to prevent the phenomena of excessive stabilization, and the Kalman filtering is adopted to smooth the image sequences. Numerical experimental results show that this algorithm can effectively smooth out the unwanted motion and follow the intentional camera movement under certain resolutions.展开更多
基金Supported by State Key Laboratory of Explosion Science and Technology Foundation(ZDKT08-05)
文摘An effective algorithm of electronic image stabilization （EIS） of catadioptric panoramic imaging system for track robots is presented. The key techniques of this algorithm are as follows：① A model of electronic image stabilization is built by analyzing the imaging theory and the principle of EIS, and the image shift function of unwrapped panoramic image is deduced;② The relationship equation between motion estimation parameters of annular panoramic image and motion estimation parameters of unwrapped panoramic image is developed according to the constrained aspect ratio of real objects, motion parameters of annular panoramic image are firstly estimated, and then motion parameters among the image shift function are carried out according to the relationship equation;③ An excessive stabilization threshold is presented to prevent the phenomena of excessive stabilization, and the Kalman filtering is adopted to smooth the image sequences. Numerical experimental results show that this algorithm can effectively smooth out the unwanted motion and follow the intentional camera movement under certain resolutions.
