An improved algorithm applied to electronic image stabilization based on SIFT

Electronic image stabilization, a new generation of image stabilization technology, obtains distinct and stable image sequences by detecting inter-frame offset of image sequences and compensating by way of image processing. As a high-precision image processing algorithm, SIFT can be applied to object recognition and image matching, however, it is the extremely low processing speed that makes it not applicable in electronic image stabilization system which is strict with speed. Against the low speed defect of SIFT algorithm, this paper presents an improved SIFT algorithm aiming at electronic image stabilization system, which combines SIFT algorithm with Harris algorithm. Firstly, Harris operator is used to extract the corners out of two frames as feature points. Secondly, the gradients of each pixel within the 8x8 neighborhood of feature point are calculated. Then the feature point is described by the main direction. After that, the eigenvector descriptor of the feature point is calculated. Finally, matching is conducted between the feature points of current frame and reference frame. Compensation of the image is processed after the calculation of global motion vector from the local motion vector. According to the experimental results, the improved Harris-SIFT algorithm is less complex than the traditional SIFT algorithm as well as maintaining the same matching precision with faster processing speed. The algorithm can be applied in real time scenario. More than 80% match time can be saved for every two frames than the original algorithm. At the same time, the proposed algorithm is still valid when there are slightly rotations between the two matched frames. It is of important significance in electronic image stabilization technology.