The invention belongs to the remote sensing image processing technical field, in particular to a remote sensing image mixed pixel decomposition method based on self-organization mapping neural network. The method integrates the self-organization mapping neural network and the fuzzy grade of membership in the fuzzy theory to work out abundance values after decomposition. Simultaneously, as the self-organization mapping neural network does not has the competitive learning characteristic of an objective function, the method is free from the problem of local extremum. In addition, the invention automatically meets the two bindings required by the mixed pixel decomposition problem, wherein the two binds are respectively the binding of non-negative abundance values and the binding of the sum ofthe abundance values being 1. The invention has a better mixed pixel decomposition effect and a higher anti-noise capacity. The new method has a particularly important application value concerning the high-accuracy ground object separation and ground target detection and identification based on multi-spectrum and high spectrum remote sensing image.