针对传统图像拼接方法只能处理光照一致图像的问题，提出了一种对环境光照鲁棒的全景图拼接算法。该算法首先使用圆环投影来获取待拼接图像的匹配特征序列，不仅克服了传统图像特征提取方法中的区域局限性问题，而且较好地实现了光照变化的图像匹配；然后使用统计参数来调整待拼接图像的整体亮度，以解决光照变化问题；最后对于传统图像融合处理中采用线性加权函数通常引起的最终拼合图像重叠区域模糊问题，构造了包含图像梯度的能量函数，用于计算重叠区域的全局最优融合因子。实验表明，该算法对光照变化图像的拼接融合能取得满意的视觉效果。

Image mosaic is the key step to panorama, while existing algorithms focus on scenes with the same illumination. This paper presents a novel method for image mosaics with notable illumination difference. First, feature points are extracted by ring projection, which overpass the local area limitation in tradition methods and gains exactly matching result for image under vary illumination conditions. Then mean and covariance are used to adjust the global brightness of the images to solve the problem of different illumination. While blending factors are gained using the energy function that contains image gradient, which conquers the blur and mackle problems in the overlap area if using the tradition linear weight function. Experiment results show that we can gain satisfying visual effect using this method in image mosaics with notable illumination difference.