基于SIFT和SURF图像拼接算法的改进算法

摘要

目前,图像拼接技术已经成为数字图像处理、计算机图形学和人工智能等领域的研究热点.介绍基于SIFT(Scale Invariant Feature Transform)特征点的图像拼接算法和基于SURF(Speeded Up Robust Features)特征点的图像拼接算法,并且对这两个算法的性能做了比较,给出各自的优劣点.最后,基于这两种算法,提出一种加快图像拼接速度和质量的算法.%At present,image stitching technology has become the research focus in the fields of digital image processing,computer graphics and artificial intelligence.In this paper we introduce the image stitching algorithms based on SIFT (scale-invariant feature transform) feature points and SURF (Speeded Up Robust Features) feature points respectively,compare the performances of these two algorithms and give their respective strengths and weaknesses.In end of the paper,based on these two algorithms,we propose an algorithm which speeds up the image stitching with better quality.