针对目前大多数特征提取算法对图像的亮度变化敏感这一问题, 提出了一种基于图像灰度直方图整体分布的参数自适应亮度稳健特征提取变换(PA-IRFET)算法。该算法首先确定灰度变换函数的形式, 通过分析图像的直方图分布来计算灰度变换函数参数,然后利用不同参数值的变换函数对图像进行变换, 建立图像的亮度空间; 最后, 以亮度空间为基础, 结合适当的特征提取算子在亮度空间进行图像特征提取以获得亮度稳健的特征。通过实验将PA-IRFET算法与Harris算子相结合进行特征点提取, 检测到的特征点个数比IRFET-Harris检测到的特征点个数大幅提高, 重复特征点的个数大约提高了20%以上。实验结果表明, 提出的算法对图像亮度变化具有较强的鲁棒性。

As most feature extraction algorithms are highly sensitive to illumination variations,this paper presents a Parameter Adaptive Illumination Robust Extraction Transform (PA-IRFET) based on the histogram of the image. The method includes three steps. Firstly, the gray transformation function and parameters are determined based on the analysis of the histogram of the image. Then, the function is used to transform the image to build an illumination-space of the image. Finally, the illumination-space is combined with feature extraction algorithms to detect illumination robust features. In the experiment of this paper, PA-IRFET is combined with Harris detector to improve the number of detected features of IRFET greatly and the number of repeated features of IRFET has been improved by about 20% on average. This demonstrates that the PA-IRFET is more robust to illumination variations than the IRFET.