On the basis of analyzing, receiving, and parsing the computer video electromagnetic leakage emission signal, an image of the screen display content can be obtained. Due to the interference noise existing in the receiving process, the received image information may be drifted, the recognition may be poor, and the definition might be low. In order to improve the recognizability of the restored image, firstly, based on image noise analysis, cumulative averaging and noise smoothing, this paper proposes an image processing method based on ambiguity for electromagnetic leakage emission reduction image. Secondly, according to image denoising implementation steps, combined with computer video reproduction example, the image processing method was verified by comprehensive experiments. Lastly, the image evaluation and signal-to-noise ratio analysis of the experimental results were carried out. The results show that the image processing method based on the ambiguity of electromagnetic leakage emission reduction image has some improvement in subjective and objective evaluation with obvious promotion.

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When the computer is working, it will transmit the electromagnetic leakage signal containing the video information and receive and process the electromagnetic leakage signal within a certain distance, which can reproduce the screen information and form the electromagnetic leakage restoration sequence image. Due to the noise in the receiving process and the fluctuation of the video line and field signal, the image of the electromagnetic leakage restoration sequence will be blurred and will drift between frames. The multi-frame cumulative averaging method can theoretically improve the signal-to-noise ratio of the reconstructed image, but the offset of the reconstructed image sequence caused by the electromagnetic leakage will bring adverse effects. Firstly, this paper analyzes the noise of electromagnetic leakage emission and restoration sequence images and the method of multi-frame cumulative averaging, as well as the cumulative averaging effect of multi-frame sequence images under the influence of image offset. Secondly, on the basis of theoretical analysis, an algorithm of image migration feature retrieval for electromagnetic leakage restoration sequence is proposed and validated, which achieves more accurate inter-frame matching, automatic offset calculation, and multi-frame sequence image accumulation and enhances the recognition of the electromagnetic leakage restoration image. Lastly, different algorithms are compared, and their effects are evaluated as well.

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