Research on fast super-resolution image reconstruction base on image sequence

The image degradation caused by Motion blur, non-ideal sample and noise was producing in the process of Image Acquirement. This paper proposed a fast super-resolution image reconstruction algorithm basing on image sequences. On the basis of image registration, Registration algorithm used Affine Transform as geometric transform Model. A sequence of low-resolution images was roughly registered basing on feature and then use Registration algorithm basing on Gray to optimize the result. Iterative back-projection technique was used to construct high resolution from image sequences. Firstly it made common low-resolution sequence images relate to standard displacements, and then reconstructed high-resolution image according to the relationship between low-resolution sequence images with standard displacement and high-resolution image. The high-frequency was distilled through the local estimation. By compensating the high-frequency component, the high-resolution images were recovered. Experimental results show that this algorithm solve the problem that the translation and rotation is small in traditional method. It has characterized over low computation complexity, fast convergence. The details, definition and resolution of high resolution image processed with the proposed method are effectively improved.