Research On Histogram Equalization Enhancement Algorithm For Irregular Illumination License Plate Image

In the process of collecting the license plate, due to lack of light or license plate collection device appear offset or license plate has stains and other reasons, lead to these uniform problems that license plate image captured appear low-illumination, dim image, mixed light and dark shade areas. Facing these problems, the pre-treatment can remove image noise information and improve signal to noise ratio of the image, enhancement image contrast, and outstanding image detail. Histogram equalization algorithm has a very important position in image pre-processing.Firstly, facing to shortcoming of traditional histogram equalization algorithm, the paper make a progress in the time domain by the basis of previous algorithm, made a variety of improved algorithms and made experimental to verification the feasibility and robustness of the algorithm, respectively make subjective evaluation and objective evaluation for merits of improved algorithm and the original algorithm. Secondly, the algorithm is improved in the frequency domain and mixed domain, primarily FT, DCT and WT to process the image, compare the pros and cons of the algorithm and then to find the optimal algorithm by hybrid computing with the aforementioned time-domain. For uneven image global algorithm is not ideal, we focus on the local process, divided sub-block is sufficiently small, thus each sub-block is linear distribution, improve the algorithm. Again, in order to solve the gray-scale loss and gray uneven distribution and other issues, we introduce artificial neural network and human visual system for image processing, the processing results in line with the human visual characteristics. Finally, for enlarged image noise at the process of equalization. We mainly used median filtering, homomorphic filtering, bilateral filtering and math morphological to remove image noise, and compared with other de-noising algorithms, seek to the best methods. We combine image de-noising with improved algorithm time-consuming and treatment effect.Experimental results show that through improved handling, a final image satisfies the requirements of equalization, it can well improves the contrast of images, suppress image noise, reduce the loss of gray level, balance histogram equalization.