The present invention relates to an illumination-robust facial image local texture enhancement method includes the following steps that: logarithmic transformation is performed on the gray value of an inputted original face image I, so that a logarithmic transformation result image I' can be obtained; Gaussian differential filtering and bilateral differential filtering are performed on the logarithmic transformation result image I', so that differential filtering result images IDoG and IDoB are obtained, image information fusion is performed on IDoG and IDoB, so that a fusion result image I" is obtained; and the fusion result image I" is divided into sub-image blocks, grayscale-equalization processing is performed on each sub-image block by means of a mean normalization method, and the sub-image blocks are spliced according to division positions, and then the pixel gray value range of a spliced image is compressed by means of a hyperbolic tangent function, and an image is outputted. With the method of the invention adopted, facial images imaged under different illumination conditions can be processed; illumination influence can be eliminated; face local texture information can be enhanced; and recognition accuracy in face recognition application can be improved. The method has the advantages of low algorithm complexity and high light robustness.