The invention discloses an image reconstruction method based on group sparsity coefficient estimation. The method belongs to the technical field of digital image processing and is an image reconstruction method based on similar block set sparsity coefficient estimation, wherein similar image blocks are searched by an Euclidean distance at first; partial and non-partial sparse representation is carried out to a similar image block set, so that the sparser and more accurate coefficient is obtained; a reconstruction model is solved further by a Bergman iteration algorithm; and the sparsity coefficient is estimated according to a linear minimum mean square error rule, so that the accurate estimation of the small coefficient containing image texture detailed information is ensured. The method disclosed by the invention has the advantages that the linear minimum mean square error estimation is carried out to the similar image block set sparsity representation coefficient, so that obvious effects are obtained in repair, deblurring and other aspects; a reconstructed image will also have the more abundant detailed information; overall visual effects become clearer; and the method can be used in the repair and the deblurring of the optical images.