The embodiment of the invention provides a half-tensor image compression method and an image recovery method based on an optimal measurement matrix. The image compression method comprises the following steps: carrying out sparse transformation on an original matrix of an image to be compressed to obtain a first sparse representation matrix of the image to be compressed; determining the row numberand the column number of the initial measurement matrix corresponding to the original matrix based on the row number, the preset compression ratio and the preset coefficient of the first sparse representation matrix; based on a preset element numerical relationship, generating an m*n-dimensional matrix as an initial measurement matrix; optimizing the initial measurement matrix to obtain an optimalmeasurement matrix; and based on the optimal measurement matrix and a preset half-tensor compressed sensing model, compressing the first sparse representation matrix to obtain a compressed target matrix. Compared with the prior art, by applying the scheme provided by the embodiment of the invention, the practicability of the compressed sensing theory in a network with limited computing resourcesand communication energy consumption can be improved.