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Based on the expected visual effect and light environment adaptation data in realistic situation, a convolution operations-based neural computing structure is developed to implement extraction and fusion of visual characteristics. And output of this part is further utilized for following digital evaluation of visual effect. At last, simulation experiments of the proposal are conducted to assess running effect of the proposal. The results show that time efficiency of proposal is reduced by 23.8% and the accuracy rate is improved by 12% compared with the U-net model. 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