The Algorithm Of X-ray Image Enhancement Based On Energy Adjustment

In the human society, the image is a good information transmission platform, at the beginning of human society, people have begun to use the image to record and transmit information in life.The vast majority of human information is derived from the image.So, the further development and progress of image processing technology is very important for human civilization.With the development of computer technology, the computer has been widely used in image processing, which promotes the rapid development of image processing technology.In the actual processing of images, the technical staff will usually use a technology- image enhancement technology, the technology can greatly improve the efficiency and quality of image processing.The main principle is based on the analysis of the target to the need to strengthen the observation, and will not be part of the need to weaken the processing,and ultimately make the image of the more targeted information.In this paper, we first discuss the current image enhancement algorithm, and the basic principles of these algorithms are described and compared, the focus of the analysis of the algorithm are: histogram equalization image enhancement algorithm; image enhancement algorithm based on frequency domain filtering; image enhancement algorithm based on the image enhancement algorithm.I studied these algorithm,and their advantages and disadvantages were analyzed, and the application of image enhancement algorithm was summarized.Through the analysis and comparison, the traditional image enhancement method has the advantages of fuzzy information and poor contrast, so the algorithm of X-ray image enhancement based on energy adjustment is proposed.In the description of the algorithm, this paper mainly calculates the three processing methods of low frequency, low frequency, high frequency enhancement and Gamma correction.In this paper, we make a comprehensive evaluation on image quality by using the MATLAB platform for image enhancement experiments. Finally, the results are compared with the experimental results, and it is found that the algorithm has better effect on the low resolution image contrast.