Blurred Image Processed Under The Pipelining Surveillance

With the development of information technology, pipeline monitoring technology is widely used in industrial production, the traditional monitoring techniques mostly rely on manual focus, and when the line is running faster, the captured images easily distorted, the distorted image will bring errors to the whole monitoring system. Firstly, two main technology of image detection and search of focus were analyzed ,then proposed a way to restore motion blurred image and defocus blurred image in pipeline monitoring.The main contents of this paper are shown as following:1, Improved the correlation detection algorithm, by a large number of experiments, and compared to the classic definition functions of gray class, the algorithm is verified reliability.2, Analyzed the principle of automatic focusing on the image, then proposed a method to search the focus based on "reward and punishment" measures. And did a simulation test the search method.3, Proposed a method to estimate the motion blurred image point spread function (PSF), based on the background of pipeline application.4, Compared and analyzed the advantages and disadvantages of classical recovery algorithm, finally we selected the Wiener restoration. Then paper analyzed the reason of Gibbs effects in the restored image. and methods of how to delete the ringing effects.5, The motion blurred image and defocus blurred image were restored by the method in the paper. At the last we use the methods of image quality evaluation, evaluated the recovery process in each step in this paper.Through a large number of experimental results, the methods of image detection, image restoration and auto focus, all can able to achieve very good results, and meet the request of real-time in the pipeline monitoring system.