It is still a very challenging task to recognize a face

in a real world scenario, since the face may be corrupted by

many unknown factors. Among them, illumination variation

is an important one, which will be mainly discussed in this

paper. First, the illumination variations caused by shadow or

overexposure are regarded as a multiplicative scaling image

over the original face image. The purpose of introducing

scaling vector (or scaling image) is to enhance the pixels

in shadow regions, while depress the pixels in overexposure

regions. Then, based on the scaling vector, we propose a novel

tone-aware sparse representation (TASR) model. Finally, a EMlike

algorithm is proposed to solve the proposed TASR model.

Extensive experiments on the benchmark face databases show

that our method is more robust against illumination variations.