To improve the quality of cell refractive index microscopy imaging and enhance feature recognition, this paper proposes a fusion method for cell refractive index and bright-field micrographs based on convolutional neural network algorithm, which overcomes the shortcomings of traditional fusion methods involving manual formulation of fusion rules, and learns adaptive strong robust fusion functions from training data to obtain better fusion results. The subjective and objective evaluation results show that the proposed method effectively improves the resolution of the cell refractive index micrographs, which in turn improves feature recognition