Image enhancement algorithm based on super resolution reconstruction

In order to improve image resolution by software processing, this paper investigates the theory and algorithms for reconstructing high resolution images from low resolution image sequences, and proposes a method to obtain high resolution images from low resolution image sequences. We realized the rough-to-fine image registration by pyramid multi-layer construction based on optical flow field, and obtained the sub-pixel motion estimation. After the multi-frame low resolution image was sub-pixel registered, we proposed a method for dynamically and adaptively determining the regularization parameter, constructed the simple regularization cost function and built the reconstruction model between low resolution image and high resolution image. The experimental results show that the horizontal and vertical resolution achieved with this algorithm is two times better than that of the original image. Compared with the traditional POCS algorithm, this algorithm reconstructs clearer image, and the computation time is reduced by 50%.