Restoration of low resolution car plate images using PCA based image super-resolution

In this paper, a car plate image restoration system is presented, in which the PCA (Principle Component Analysis) based super-resolution method is applied to restore very low resolution car plate images (height <; 10 pixels) from mainland China and Hong Kong. Several algorithms are proposed to improve the robustness and performance of this system. The core part of this system is a dynamic PCA algorithm, in which the training set is adjusted adaptively for achieving better restoration results. Extensive experiments on both simulated test images and practical test images show that our system performances satisfactorily in terms of the restoration error rate and the flexibility in practical applications.