To solve the problems of texture detail loss and poor visual perception of fused images in complex background,an infrared/visible image fusion algorithm based on multi-layer convolution is proposed.The network framework of the algorithm is divided into encoder,decoder and fusion network.An Efficient Channel Attention (ECA) mechanism is introduced into the encoder to encode the source image.Multi-layer Convolutional Fusion Network (MCFN) is formed by fusion of multi-layer convolution blocks,gradient convolution blocks,down sampled convolution block and the attention mechanism of convolution space channels.Feature fusion is performed through MCFN.Then the output fusion image is reconstructed through the decoder.Eight objective evaluation indicators are selected for comparison with five existing algorithms on two datasets.The results show that the fusion image of the proposed algorithm has prominent object,clear details and obvious contour,and the index is improved significantly,which accords with human visual perception.