The near infrared images enhancement of teeth based on improved successive mean quantization transform

In allusion to the problem that the near infrared images of early teeth disease detection is low contract, minutiae feature isn’t evident and the images have small target gray range. So the image enhancement approach is proposed, which is disposed by the high frequency filter, linear compensation and the successive mean quantization transform. First, the near infrared images of teeth are filtered by the high frequency filter, the high frequency filter can emphasize on high-frequency components and keep lost low-frequency components, then the near infrared images are linearly compensated, finally the method combined with the successive mean quantization transform to enhance the near infrared images. The experiments show that the enhancement images show high contract and detail feature is obvious. Visually it is better to observe whether the teeth are diseased. Compared with the results of histogram equalization, the proposed method can get better enhancement effect and the particular features are stand out.