The present invention discloses an image super-resolution reconstruction method and a system. According to the method, firstly, the pixel data of a plurality of low-resolution images having the complementary information are acquired. Secondly, according to the pixel data, data consistency items selectively integrating brightness constancy constraints with gradient constraints are constructed and matched feature points are subjected to the initial flow vector updating treatment. Initial flow vectors are substituted into a motion estimation variation model constructed based on data consistency, and then the optimal motion flow vector of each pixel is obtained. Simultaneously, an optimal fuzzy core is constructed based on the brightness of the L0 norm and the fuzzy estimation energy function of a gradient-combined constraint image prior model. Finally, according to the optimal motion flow vector and the optimal fuzzy core, a reconstructed high-resolution image of a variational model is established. Based on the method or the system, the accuracy of motion displacement vectors and the accuracy of fuzzy parameters during the super-resolution reconstruction process can be effectively improved. As a result, an optimal super-resolution reconstruction result is obtained.