Color correction in image stitching using histogram specification and global mapping

Color correction is an important problem in image stitching. There is a color inconsistency issue between the images (good quality as a reference image and bad quality as a test image) to be stitched. This paper presents a color correction approach with histogram specification and global mapping. The proposed algorithm can make images share the same color style and obtain color consistency. There are four main steps in this algorithm. Firstly, overlapping regions between a reference image and a test image are obtained. Secondly, an exact histogram specification is conducted for the overlapping region in the test image using the histogram of the overlapping region in the reference image. Thirdly, a global mapping function is obtained by minimizing color differences with an iterative method. Lastly, the global mapping function is applied to the whole test image to produce a color corrected image. Both synthetic dataset and real dataset are tested. The experiments demonstrate that the proposed algorithm outperforms other methods both quantitatively and qualitatively.