Denoising Of Real-time X-ray Imaging Technology Research

In the actual X-ray detection process, because X-ray real-time detection system is affected by many kinds of qualitative factors, these factors affect the quality of the images,lead to larger background ups and downs and image noise to X-ray image,bring inconvenience for subsequent deal. Thus improving X-ray imaging detection sharpness is key to denoise. Effectively suppressing X-ray image noise is the key in this paper. Based on image intensifier industrial X-ray detection system as the research object. Focuses on the analysis of X-ray imaging system the basic principle and noise sources, improved the X-ray image noise restraining algorithm.Aiming at the characteristics of X-ray image noise, firstly this paper analyzes the conventional X-ray image filtering algorithm, and obtains advantages and disadvantages of each algorithm. Second, a single algorithm can not effectively restrain the X-ray image noise, come up with rapid median recursive filtering algorithm and wavelet recursive filtering algorithm . Finally, using the background modeling to detect moving objects and the principle of Mean-Shift object tracking. Real-time tracking moving region and NL-means dynamic noise reduction .Using rapid median recursive filtering algorithm and wavelet recursive filtering algorithm to X-ray image noise, image signal-to-noise ratio is improved, noise got better inhibition .Using the background modeling detect moving objects and Mean-Shift object tracking method The noise of the moving region is suppressed, clarity is effectively improved.