Blind video super resolution reconstruction based on error-parameter analysis method

In order to improve the spatial resolution of videos, a blind video super-resolution reconstruction method is proposed. Utilizing the redundancy information between the adjacent frames in low resolution video and the prior information of imaging system, a high resolution video can be reconstructed. Using Wiener filter image restoration method, under the condition of different parameters of point spread function (PSF), multiple error-parameter curves are generated. Through analyzing the relationship between these curves and by setting some thresholds, the PSF of the imaging system is estimated automatically. Experiments are performed on simulated images and color video and practical video respectively. The experimental results demonstrate the effectiveness of our approach and also show the great importance of PSF estimation in video super-resolution reconstruction. This error-parameter analysis method may also be well extensively used to estimate other types of PSF, only if the PSF can be denoted by parameters.