ing at the face images in large angle oblique illumination and extremely dark and uneven illumination environment, an illumination compensation method is proposed based on anisotropic Retinex transform. First, according to the statistical characteristics of face image, the direction of the light source is analyzed, and the edge is detected by Prewitt operator. Combined with the geometric characteristics of the face texture, the curvature, slope and symmetry are introduced to achieve the unevenness of the face and illumination, thus distinguishing the false edge of the face. Second, based on the Weickert structure tensor, an improved anisotropic diffusion model is implemented based on different types of edges. The model is combined with Retinex algorithm to realize face image illumination compensation. The experimental results show that the improved anisotropic diffusion method can enhance the image brightness, prominent texture detail, and eliminate most light shadow at the same time enhancing face edge.
Mei Yang, Zefu Tan, Li Cai, Xue Yao. Illumination Compensation for Face Images Based on Anisotropic Retinex[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121007