The invention discloses a locality-constrained and low-rank representation based human face super-resolution reconstruction method. The method comprises a first step of acquiring a to-be-reconstructed low resolution human face image, comparing the to-be-reconstructed low resolution human face image with each of a plurality of high resolution human face images, and finding out overlapping image blocks; a second step of respectively calculating representation weight coefficients of the overlapping image blocks under conditions of locality constraint and low-rank constraint and resolving the representation weight coefficients so as to obtain an optimal weight coefficient; a third step of synthesizing overlapping image blocks on the high resolution human face images corresponding to the representation weight coefficients by combining with the optimal weight coefficient and overlapping times, so as to obtain high resolution human face image blocks; and a fourth step of performing position splicing on the plurality of high resolution human face image blocks obtained through synthesis, so as to obtain a complete high resolution human face image. Through adoption of the method, higher quality of high resolution human face image can be obtained.