Automatic Quaternion-Domain Color Image Stitching

Taking advantages of the quaternion representation of the color image, this paper proposes a quaternion perceptual seamline detection model to generate the seamline in the quaternion domain. It considers seamline detection as a quaternion-domain color image labeling problem and minimizes the local-area quaternion perceptual difference cost to obtain the optimal seamline. To assess seamline quality effectively, we develop a quaternion perceptual seamline quality measure. Based on the proposed quaternion perceptual seamline detection model and quality measure, we further propose a general framework for automatic quaternion-domain color image stitching (AQCIS). To the best of our knowledge, this is the first attempt to perform color image stitching completely in the quaternion domain. Meanwhile, AQCIS introduces the joint optimization strategy of local alignment and seamline in an iterative fashion. Extensive experiments on challenging datasets demonstrate that our AQCIS achieves superior performance for color image stitching in comparison with state-of-the-art methods.