一种基于主成分分析的图像光照校正算法

An Image Illumination Correction Algorithm Based on Principal Component Analysis

针对受相同光照条件干扰图像的光照校正问题,提出一种基于主成分分析的图像光照校正算法.首先,利用给定的多张图像构造协方差矩阵,并计算特征值和特征向量;然后,根据特征向量构造一组标准正交基;最后,选择部分基底(主成分)重构图像.实验结果表明,该算法能很好地消除光照影响,同时保留图像的主要特征.与经典算法进行对比验证了该算法的有效性.

Aiming at the illumination correction problem of the image interfered by the same illumination conditions,we proposed an image illumination correction algorithm based on principal component analysis.Firstly,a covariance matrix was constructed by using given multiple images,and the eigenvalues and eigenvectors were calculated.Secondly,a set of normal orthogonal bases was constructed according to the eigenvectors.Finally,a part of substrate principal component was selected to reconstruct the image.The experimental results show that the algorithm can eliminate the influence of illumination and retain the main features of the image.Compared with the classical algorithm,the effectiveness of the algorithm is verified.