The invention discloses a single-frame image super-resolution reconstruction method on the basis of deep learning. The single-frame image super-resolution reconstruction method comprises the following steps: 1, firstly, acquiring characteristics of low-resolution and corresponding high-resolution image blocks by training two automatic encoders; 2, on the basis of the acquired characteristics of the high-resolution and low-resolution image blocks, then training a single-layer neural network and learning a nonlinear mapping relation of two characteristics; 3, on the basis of two automatic encoders and the single-layer neural network, constructing a three-layer deep network, using the low-resolution image block as an input, using the high-resolution image block as an output and finely regulating parameters of the three-layer deep network; 4, according to the obtained three-layer deep network, carrying out single-frame image super-resolution reconstruction, and obtaining the output, i.e. a gray value corresponding to the high-resolution image block, by using a gray value of the low-resolution image block as the input. According to the single-frame image super-resolution reconstruction method on the basis of deep learning, not only is quality of a super-resolution reconstructed image improved, but also super-resolution reconstruction time is shortened and the real-time requirement can be met basically.