The invention belongs to the technical field of image super-resolution reconstruction, and discloses an image super-resolution reconstruction method based on deep convolution sparse coding, and the method comprises: embedding a multilayer learning iteration soft threshold algorithm ML-LISTA related to a multilayer convolution sparse coding model ML-CSC into a deep convolution neural network DCNN; adaptively updating all parameters in the ML-LISTA by using the learning ability of the DCNN, and constructing an interpretable end-to-end supervision neural network SRMCSC for image super-resolution reconstruction; and introducing residual learning, extracting residual features by using an ML-LISTA algorithm, combining the residual and an input image to reconstruct a high-resolution image, and then accelerating the training speed and the convergence speed. The SRMCSC network provided by the invention is compact in structure, has good interpretability, can provide a result with visual attraction, and provides a practical solution for super-resolution reconstruction.