A novel adaptive illumination normalization approach is proposed to eliminate the effects caused by illumination variations for face recognition. The proposed method divides an image into blocks and performs discrete cosine transform(DCT) in blocks independently in the logarithm domain. For each block-DCT coefficient except the direct current(DC) component, we take the illumination as main signal and take the reflectance as "noise". A data-driven and adaptive soft-thresholding denoising technique is employed in each block-DCT coefficient except the DC component. Illumination is estimated by applying the inverse DCT in the block-DCT coefficients, and the indirectly obtained reflectance can be used in further recognition task. Experimental results show that the proposed approach outperforms other existing methods. Moreover, the proposed method does not need any prior information, and none of the parameters can be determined by experience.
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机译:应用项目反应理论对友谊质量量表修定—以结构方程模型、层面理论多种技术支持修定量表的质量 Modifying Friendship Quality Questionnaire with Item Response Theory Approach——Validating with Facet Theory and Structure Equation Techniques