An improved low-light image enhancement (LLIE) algorithm based on the hybrid strategy of deep learning and image fusion was proposed in this paper. We first adopted illumination prediction model to quickly estimate the optimal illumination component from a given low-light image and obtain its corresponding moderately exposed image within the framework of the Retinex model. Then the low-light image and its over-exposed image were used as supplementary images for the moderately exposed image. Finally

the three images were fused within the framework of the local structured fusion and the chrominance weighted fusion mechanism to obtain the final enhanced image. Experimental results demonstrate that

compared with the state-of-the-art LLIE algorithms

the proposed hybrid strategy has significant advantages in both subjective and objective image quality evaluation metrics with better image edge preservation and color fidelity effect on local image details.