自适应柱状全景图拼接

为了实现高效高精度的全景图拼接,提出了一种面向柱状全景图的自适应拼接方法。该方法首先使用基于灰度边缘特征点的图像匹配来获得匹配坐标,并由匹配坐标唯一性计算焦距;然后在该焦距参数估计的基础上,采用新的自适应混合图像灰度匹配方法生成初期拼接图像,并根据其宽度以及相关判别条件进行焦距估计的调整,再重复迭代,以获得准确的焦距参数;最后利用基于角度1维投影的图像匹配方法进行匹配坐标的小范围校正,以及使用线性平滑算法生成最终柱状全景图。该法在精确焦距的基础上,结合了多种图像匹配算法,并根据自相关指数自适应选取结果,实现了水平和垂直两方向上的匹配定位和错位检测。实验证明,该方法不仅在真实图像上的可行,且具有较高的实时性、精度和鲁棒性。

Adaptive Cylindrical Panoramas Mosaic

In this paper,the problem of efficiently and precisely constructing the cylindrical panoramas view of a scene from an image sequence is considered.The proposed method firstly detects correspondences based on gray level edge feature so that the focal lens can be counted based on correspondences uniqueness.Then the focal lens will be directly used in following image matching processing with a novel adaptive mixed gray level image matching algorithm and outputs a rough panorama result.The width of it reacts to a judgment to adjust the focal lens,which induces an iterative computation to guarantee an exact focal lens.Finally an angle-oriented one-dimension projection template matching algorithm will be employed to modify the correspondences in narrow range and the final panorama is obtained by linear image blending.Adaptive using multiple image matching algorithms according to self-relation variant after precise focal lens searching,the method redraws the accurate overlapping image horizontally and vertically.Experimental results proved that the proposed approach are given works well over most image sequence capture by handholding camera,and is fast,accurate and robust enough for real time applications.