Abstract
It is hard to distinguish the character from the car license plate image which has poor quality. We propose a method using classified bases and example-based super-resolution to reconstruct a high-resolution car license plate image. We use the Bayesian classifier to classify the single character of the license plate in Orthogonal Locality Preserving Projections (OLPP) subspace. The proposed cost function in the refinement step correct the classified result in the following. According to the classified result of final class decision step, we can select the most suitable basis set to reconstruct a high-resolution car license plate image. The experimental results can show that the reconstructed image via our proposed method is better than the result which reconstructed by calculating the whole car license plate image.