The invention discloses an image noise estimation method based on a deep convolutional neural network. The method is used for solving the technical problem that an existing image noise estimation method is poor in practicability. According to the technical scheme, a loss function is constructed by combining a noise error and a noise level error to train a deep convolutional neural network; the trained deep convolutional neural network obtains a noise map with accurate numerical distribution and accurate statistical mean square error from the noise pollution image; a deep convolutional neural network is adopted; convolutional kernel expansion values are firstly multiplied layer by layer and then symmetrically decreased layer by layer in an equal proportion mode, the extraction capacity of the deep convolutional neural network for random noise is improved, the number of convolutional kernels of each convolutional layer is large, a distribution model and the level of noise used in training are completely random, and the generalization capacity of the deep convolutional neural network for random noise is improved. According to the method, the noise image is extracted from the noise pollution image, the flexibility of modeling and analyzing the noise in subsequent operation is improved, and the practicability is good.