基于梯度区域分割的拼接图像颜色校正

Color correction for stitching images based on gradient region segmentation

在室外场景拼接的颜色校正中,由于图像间的亮度差异往往较大,校正结果易出现噪点及色块。针对该问题,提出一种梯度区域分割的颜色校正方法。结合图像的梯度和颜色信息将图像分为两个区域,使得具有相似的梯度范围和颜色特性的区域相匹配;对颜色单一区域采用简单的统计特征校正方法,对颜色复杂区域采用改进的多维概率密度转换法,避免区域间相互影响。利用不同场景下的图像进行实验并与多维概率密度转化法做对比,对比校正后的拼接图像及量化指标,实验结果表明,该方法能够减少颜色失真,保持原图结构特征,有效提高颜色校正效果。

For color correction in the stitching of outdoor scene,there may be grain noise and block artefacts in result images because of the large difference of brightness between images.To solve this problem,a method of color correction using gradient region segmentation was proposed.The gradient and color information were combined to divide each image into two regions to match the areas with similar gradient level and color character.To avoid the mutual influence between regions,simple statistical characteristics correction method was used for regions with simple color,while modified multidimensional probability density function transfer was used to deal with regions with complex color.The approach was tested on a number of different scenes and compared with multidimensional probability density function transfer method.The stitching results after correction and quantitative indexes were given to evaluate two methods.The experimental results show that the method works well to reduce the color distortion and keeps the structure of the original image,thus it obtains better performance of color correction.