The research and implementation of super-resolution reconstruction for multi-frame blurring images

Authors:
Rong Wang;Xiaogang Yang
Affiliations:
Chinese people's public security university, Beijing, China;Chinese people's public security university, Beijing, China
Venue:
Proceedings of the 2011 International Conference on Innovative Computing and Cloud Computing
Year:
2011

Citing 3
Cited 0

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
A frequency domain approach to registration of aliased images with application to super-resolution

EURASIP Journal on Applied Signal Processing
Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we design a super-resolution restoration system for multi-frame blurring images. There are two modules in this system, namely that motion estimation and reconstruction of super-resolution. Firstly, the motion parameters are estimated by a frequency algorithm; then a high-resolution image is reconstructed from low-resolution images based on the motion parameters by four different super-resolution reconstruction methods. The experimental results show that the restoration effect of POCS is better than the two restoration effects obtained by IBP method and the one presented in reference [9]. The bi-cubic interpolation method can get the best restoration effect based on the same motion estimation method under the condition that all low-resolution images have same blurring reason and noise feature. It can be known that bi-cubic interpolation reconstruction method is suitable than the other three methods for multi-frame images with same blurring reason and noise.