基于角点匹配图像拼接方法的改进

在图像拼接领域,同时提高图像拼接的质量和速度是比较困难的。为了解决这个问题,本研究对图像拼接中的特征匹配和图像融合这2个关键部分进行了改进。在特征匹配方面,传统的用于提纯出匹配特征点的方法是使用RANSAC算法。为了解决其在不匹配点比例较大时提纯效率较低的缺点,本研究提出了一种使用聚类法预提纯特征点再用RANSAC算法精确提纯的方法,在图像融合时,使用了最佳路径法与亮度权重函数相结合的方法,以达到消重影并使拼接结果图像自然的目的。试验证明,经过对图像拼接以上2部分的改进算法效率有极大的提高,并能有效地去除重影使拼接图像更加自然。

The improvement of a feature-based image mosaics algorithm

In image mosaics,it is very hard to improve both the quality of mosaics and the runtime. This paper discusses the two key parts of image mosaics to solve these problems:feature matching and image blending.In feature matching,a traditional method to purify feature points is RANSAC algorithm in feature-based image mosaicing.To prevent its low efficiency,this paper presents a pre-pure feature points method by clustering to enhance it.In image blending,to de-ghost and present a natural stitched picture,optimal route and brightness weighting function methods are ac- tualized.Experiment results show that after improving the two parts of image mosaics algorithm, the efficiency is greatly enhanced and the ghosting is removed effectively to make the blended pic- tures inartificial.