Dynamic target image correction method of digital media based on virtual reality

Abstract

In order to overcome the problems of low peak signal-to-noise ratio (PSNR), low structure similarity index and resolution coefficient not close to 1, a digital media dynamic target image correction method based on virtual reality is proposed. This method uses virtual reality, image neighbourhood information statistical information, fuzzy information and human visual characteristics to carry out grey value statistics, then combines with the statistical characteristics of grey value to realise image denoising processing; combined with rational function model, obtains the digital media dynamic target image pixel coordinates representing the ground point coordinates, obtains the target image correction model, completes the digital media dynamic target image correction. The experimental results show that the peak signal-to-noise ratio (PSNR) is close to 400 dB, the maximum structure similarity index is 0.6025, and the decision coefficient is close to 1, which can quickly and accurately realise the dynamic target image correction of digital media.