基于拼接缝自适应消除和全景图矫直的快速图像拼接算法

针对图像拼接存在色差过渡不均匀、图像倾斜扭曲及拼接效率低的现象,提出一种基于拼接缝自适应消除和全景图矫直的快速图像拼接算法。首先,用尺度不变特征变换(SIFT)提取图像指定区域特征点并用双向K近邻(KNN)算法进行图像配准,有效提高算法效率;其次,利用动态规划思想提出自适应公式找到最优拼接缝并用图像融合算法对其自适应消除,解决拼接缝色差过渡不均匀问题;最后,针对累积拼接误差形成全景图倾斜的现象,利用边缘检测算法提出自适应拟合四边形矫直模型,把原始全景图矫直为一个全新的全景图。所提算法与分块图像拼接和二叉树图像拼接算法相比,图像质量提升了5.84%~7.83%,拼接时间仅为原来的50%~70%。实验结果表明,该算法不仅通过自适应更新机制减少不同图像背景下拼接缝色差过渡不均匀的现象,从而提高了图像质量;而且提高了拼接效率,降低了全景图倾斜扭曲程度。

Fast image mosaic algorithm based on adaptive elimination of stitching seam and panorama alignment

Aiming at the phenomenon that image mosaic, to a certain extent, has uneven chromatic aberration, distortion and low efficiency, an adaptive elimination of image stitching seam and panorama alignment based fast image mosaic algorithm was proposed. Firstly, the Scale-Invariant Feature Transform (SIFT) was used to extract feature points of the specified area of the image and image registration was performed by using bidirectional K-Nearest Neighbor (KNN) algorithm, effectively improving the algorithm efficiency. Secondly, focusing on the uneven chromatic aberration transition of stitching seam, an adaptive formula for finding the optimal stitching seam was proposed based on dynamic programming, and then the seam was adaptively eliminated by image fusion. Finally, for the phenomenon of panoramic tilt caused by accumlated stitching error, an adaptive fitting quadrilateral alignment model based on edge detection algorithm was proposed to make the original panorama into a completely new panorama. Compared with the image mosaic algorithm based on block and the image mosaic algorithm based on binary tree, the proposed algorithm has the image quality improved by 5.84%-7.83% and the stitching time shortened to only 50%-70% of the original. Experimental results show that the proposed algorithm not only reduces the unevenness of chromatic aberration transition of stitching seam in different image backgrounds through adaptive update mechanism, so as to improve the image quality, but also increases the stitching efficiency and reduces the distortion degree of panorama.