Existing face recognition systems can achieve high recognition rates in the well-controlled environment. However, when the resolution of the test images is lower than that of the gallery images, the performance degrades seriously. Traditional two-step solutions (first adopting super-resolution (SR) method, and then performing the recognition phase) mainly focus on visual enhancement, rather than classification. In this paper, we utilize Local Consistency Preserved Coupled Mappings (LCPCM-I) to project the face images with different resolutions onto a new common space for recognition based on coupled mappings (CM). To achieve better results, we incorporate discriminant information with LCPCM (LCPCM-II). The experimental results on FERET database verify the effectiveness of our proposed method. © 2013 APSIPA.