Histogram Equalization and Image Feature Matching

The algorithms of image feature matching have good stability with scale, illumination change and rotation. They can be improved continuously in practical application. In the acquisition process of the image, the different conditions make the appearance of the same area seem different in different images. These conditions include the position, posture and performance of the camera and so on. However, the correspondence area of the image may have the projective distortion. The accuracy of image feature point's extraction and matching will be affected severely. In order to improve image quality, the original image will be processed to facilitate the application of the following steps. In this paper, the histogram equalization method is adopted to preprocess the original image to enhance the useful information. Then the preprocessed image is used respectively to the SIFT algorithm and the ASIFT algorithm to achieve the extraction and matching of the image feature points. The purpose of image preprocessing is to increase the matching number of image feature point, and improve the matching rate of image feature. The experimental results show that the image processed by the histogram equalization can improve obviously the matching number of the image feature point.