Research On Industrial Radiographic Image Sharpening Enhancement Algorithm

With the development of the X-ray imaging technology, the X-ray detection technology plays a very important role in the industrial detection, medical imaging, security, aerospace and so on, it has blended in our life and become a indispensable part of our production and life. However, due to the complexity of the object to be tested, the hardware of the X-ray detection system and other factors, the quality of the output images will drop, for instance, image edges and details become blurred, the contrast becomes low, the noise becomes great and so on. Therefore, the output image should be processed in order to satisfy the specific requirements.This paper firstly describes the development situation and the basic methods of the industrial radiographic image enhancement, then it deeply studies the theory and techniques of the industrial radiographic image enhancement, after analyzing their existing shortcomings and problems in the practical application, it proposes some improved methods of the industrial radiographic image enhancement. The work of this paper includes the following parts:1. It studys a new method of the gray range segmentation based on the novel human visual characteristics which is named as Munsell's scale, and applies this new method to the industrial radiographic image enhancement, then it proposes an improved nonlinear image sharpening enhancement algorithm combined with this Munsell's scale. Experiment results show that the image effect through the improved algorithms is much better than that through the original algorithm;2. It researchs two improved methods of the unsharp masking enhancement. The first method improves the edges and details of the industrial radiographic image through adaptively adjusting the enhancement factor, this method can adaptively adjust the sharpened intensity of the edges and details to get better enhancement effects. The second method improves the edges and details of the industrial radiographic image by combining with the piecewise linear gradient filter, this method contains some controllable parameters and can get better enhancement effects through adjusting these parameters. Experiment results show that the image effect through the improved algorithms is much better than that through the basic algorithm;3. It proposes a new unsharp masking enhancement method combined with the nonlinear gradient filter which can control the image noises. This method not only can sharp and enhance the edges and details of the industrial radiographic image but also can limit the noises increased. Experiment results show that this method has better enhancement effect and noise control ability for the industrial radiographic image.