Illumination compensation and normalization using logarithm and discrete cosine transform

This paper presents a novel illumination normalization approach for face recognition under varying lighting conditions. First, we demonstrate that illumination compensation can be efficiently implemented in the logarithm domain. In the proposed approach, discrete cosine transform (DCT) is employed to compensate for illumination variations in the logarithm domain. Since illumination variations mainly lie in the low-frequency band, an appropriate number of DCT coefficients are truncated to reduce the variations under different lighting conditions. The salient feature of our approach is that it does not need any training or modelling step and can be easily implemented with high speed.