Adaptive illumination normalization approach based on denoising technique for face recognition

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.     

Deformable Registration of Chest Radiographs Using B-spline Based Method with Modified Residual Complexity

Accurate registration of chest radiographs plays an increasingly important role in medical applications.However, most current intensity-based registration methods rely on the assumption of intensity conservation that is not suitable for alignment of chest radiographs. In this study, we propose a novel algorithm to match chest radiographs, for which the conventional residual complexity(RC) is modified as the similarity measure and the cubic B-spline transformation is adopted for displacement estimation. The modified similarity measure is allowed to incorporate the neighborhood influence into variation of intensity in a justified manner of the weight, while the transformation is implemented with a registration framework of pyramid structure. The results show that the proposed algorithm is more accurate in registration of chest radiographs, compared with some widely used methods such as the sum-of-squared-differences(SSD), correlation coefficient(CC) and mutual information(MI)algorithms, as well as the conventional RC approaches.