Color Consistency Correction Based on Remapping Optimization for Image Stitching

Color consistency correction is a challenging problem in image stitching, because it matters several factors, including tone, contrast and fidelity, to present a natural appearance. In this paper, we propose an effective color correction method which is feasible to optimize the color consistency across images and guarantee the imaging quality of individual image meanwhile. Our method first apply well-directed alteration detection algorithms to find coherent-content regions in inter-image overlaps where reliable color correspondences are extracted. Then, we parameterize the color remapping curve as transform model, and express the constraints of color consistency, contrast and gradient in an uniform energy function. It can be formulated as a convex quadratic programming problem which provides the global optimal solution efficiently. Our method has a good performance in color consistency and suffers no pixel saturation or tonal dimming. Experimental results of representative datasets demonstrate the superiority of our method over state-of-the-art algorithms.