摘要
Abstract
Parallax image stitching usually utilizes the feature-based transformation.Existing works focused on the image transformation model, especially a homography, but this is inadequate to obtain better alignment.This paper presents a new stitching method.Firstly, detect and match features in images, then RANSAC and distance similarity are used to investigate the accuracy of matching features.Then, based on these matching point pairs, moving least squares is used to construct a global affine transformation to align two images and get the overlapped region of them.Finally, constructing a network flow whose vertices are the pixels on the overlapped region, and max-flow/min-cut algorithm is adopted to search for a best seam, then stitch and blend images according to this seam.As our method effectively strengthens the matching reliability between SIFT points, the alignment accuracy of two images is better than previous method.Image stitching result is smooth and authentic, no distortion, ghosting or other artifact.关键词
图像拼接/特征点匹配/移动最小二乘法/拼接曲线Key words
Image stitching/Feature matching/Moving least square method/Stitching curve分类
信息技术与安全科学
