Research And Realization Of Super-resolution Reconstruction Algorithm Based On Image Sequences

Super-resolution reconstruction based on image sequences is the technology which reconstructs a high-resolution image from the low-resolution images or video sequences with mutual displacements. The SR's aim is to improve the process of image acquisition and transmission of image degradation caused to be clearer high-resolution images.This technology is an important branch of the image processing technology, it is not only used on the areas of remote sensing, military, public safety, medical image, multimedia image compression, but also plays an important role in the theoretical research. Although, there were many valuable research results proposed in recent years. But because of the complexity of super-resolution reconstruction, there are still significant issues needs to further study.In this article, first, the research background and significance of the super-resolution reconstruction, also the frequency domain algorithm and the various algorithms of the spatial were introduced. Through combined with the image degradation model and analyzing the advantages and disadvantages of various algorithms, the reconstruction algorithm based on maximum a posteriori probability (MAP) are selected. The MAP algorithm provides well-behaved frameworks which can combine the priori information more effectively in order to solve the optimal estimation of the reconstructed image simply.Second, data pre-processing of the low-resolution image sequence was achieved before the super-resolution reconstruction. A method which can discard the bad frames was presented for improving the effectiveness and stability of the super-resolution reconstruction. The topic of motion parameter estimation between image sequences was discussed and an effective three-step search algorithm which can reduce the motion estimation algorithm for computing the complexity and improve the image sequences of the reliability of the super-resolution reconstruction is presented in the next length. Experimental results show that the new algorithm not only ensures the search accuracy but also reduces calculation time by a large margin.Finally, according to the image statistical model, the target equation of the super-resolution reconstruction was established. In the process of solution of equation, a fast iterative method and an improved algorithm based on bilinear interpolation make the edge part and the details of the image are still clear. Under the premise of ensuring the quality of the reconstruction image, the convergence rate of the solution is improved. In the section of the experimental results, the new motion estimation algorithm can not only ensure the search accuracy but also reduce calculation time by a large margin. The improved interpolation algorithm can maintain the original image edge features, and need less computational. In the reconstruction of sequence image experiments, the algorithm need only little time to achieve convergence than the Huber-Markov algorithm, it can not only improve stability of the algorithm, but also reduce the algorithm computational. In the end, more objective and stable evaluation results were obtained from a subjective and objective evaluation of the reconstruction images.