A Study On Sharpening The Image Captured From Video Leakage

The technology of information leakage which is caused by leakage from information processing equipment (to be intercepted and reconstructed) is called TEMPSET. Research on TEMPSET is not only in favour of the application of interrelated technologies and disciplines, but also can accelerate processing of society informationization. What is more important is that it is benefit to a complete and dependable information security system. In our laboratory, some research had been made on capturing the leakage information from computer video and the recovering distance had come up to 25 meters. However, there was little study on noise reducing and sharpening of captured images. This paper will pay more attention to sharpen the images which were captured in the leakage.This paper bases on the following two aspects: signal processing and image processing. The theory of image sharpening from the captured computer information has been emphatically discussed, and some key technological points of sharpening image were also elaborated. Concrete analysis of the approach to the video signal de-noising in theory was made, and cross-correlation, auto-correlation and wavelet processing algorithm were proposed. Then a simulation of the wavelet signal processing algorithm was made, and result of signal processing by using different wavelet algorithms was obtained. I elaborated on the image post-processing method, bringing forward to dealing with the captured image in two ways, then analyzed the two theories.After theoretically analyzing, I focused on the post-processing of the captured image, introducing the concept of the signal to noise ratio and information entropy to evaluate the improvement of image quality. The captured image was processed using Filter, Fourth-order PDE and Wavelet in MATLAB, After analyzing the results, I found that the Fourth-order PDE de-noising algorithm was a better method. In the image enhancement processing, three algorithms - the Contrast Enhancement, Histogram Enhancement and Wavelet Enhancement were used. The conclusion was that the Wavelet Enhancement was a better method. In the end of the paper, by using all the methods above, a comprehensive analysis was made to draw optimization groups to processing the captured image.