基于多相机阵列型仿生复眼的图像拼接方法OA

With the rapid advancement of autonomous driving,security surveillance,and virtual reality technologies,the demand for wide-field-of-view imaging systems continues to grow to achieve broader visual perception ranges.Inspired by the compound eyes of insects in nature,a bionic compound eye imag-ing system is designed based on a multi-camera array.Comprising eight cameras arranged in a spherical ring to mimic the natural compound eye structure,a wide field of view of 105°×100° is achieved in this system.To address common issues in wide-field image stitching,such as poor quality,ghosting,and chromatic aberration,a coarse-to-fine image stitching method guided by agglomerative hierarchical cluster-ing,named AHC-LightGlue,is proposed.Firstly,key points and descriptors are extracted from the images using SuperPoint.Before feature matching,the topological structure of feature points is con-structed by the agglomerative hierarchical clustering algorithm.Coarse matching is performed at the clus-ter level to lock corresponding regions,followed by fine matching within these regions using LightGlue to address high mismatch rates and misalignment issues.Subsequently,the homography matrix is calculated by marginalizing sample consensus.Finally,a natural transition between the reference and target images is obtained by the proposed adaptive weighting fusion method.In this approach,superior fusion results are delivered even under significant brightness differences,large-scale color discrepancies are reduced,and image stitching quality is further enhanced.Experiments demonstrate that both image quality and stitching accuracy are improved by the proposed algorithm and color discrepancies are effectively reduced in image stitching to form smoother and more natural stitched images.Compared to traditional methods,the image stitching method based on a multi-camera array bionic compound eye has great robustness and adaptability.