Abstract: In order to improve the performances of face recognition under non-uniform illumination conditions，a face recognition method combining illumination compensation with features extraction robust to change in lighting is proposed.Firstly，the original images are pre-processed by illumination compensation using Discrete Cosine Transform（DCT） in the logarithm domain.Secondly，cubic spline dyadic wavelet is applied to extract an approximiation subband and three detail subbands which are robust to illumination variations.And then，2DLDA is used to reduce dimension and four classifiers are constructed.At last，the result can be obtained by fusion of four classifiers.The proposed algorithm is tested on CAS-PEAL and YaleB face databases，and achieves 83.91% and 100% recognition rate respectively.The experiments prove that the proposed method is robust to varing lighting conditions.