基于高斯二阶差分特征算子的图像拼接方法

Chen Yong, H. Hao, Zhan Di
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引用次数: 1

摘要

为了将同一场景中具有重叠区域的图像序列快速准确地合成出宽视角、高分辨率的图像,提出了一种基于D2oG兴趣点检测器的改进SIFT算法。利用改进的SIFT算法提取图像特征点并生成相应的特征描述子。然后,利用随机一致性(RANSAC)算法对特征点匹配对进行纯化,并计算变换矩阵h。最后,利用滑进滑出的图像融合算法完成图像的无缝拼接。分别用传统SIFT和本文提出的方法对经过四种典型变换的图像进行处理。结果表明,与SIFT算法相比,该算法的特征对数量更少,拼接时间更短,匹配效率更高。该方法在降低操作复杂度的同时,提高了图像拼接的实时性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Mosaic Method Based on Gaussian Second-order Difference Feature Operator
To compose the wide visual angle and high resolution image from the sequence of images which have overlapping region in the same scene quickly and correctly, an improved SIFT algorithm which is based on D2oG interest point detector was proposed. It extracted the image feature points and generated corresponding feature descriptors by improved SIFT algorithm. Then, using the random consistency (RANSAC) algorithm purified feature point matching pairs and calculating the transformation matrix H. Last, complete the seamless mosaic of images by using the image fusion algorithm of slipping into and out. It respectively process the images which had the four typical transformations with the traditional SIFT and the proposed method. The result indicated that the number of feature pairs is fewer than SIFT algorithm and the mosaic time is shorter, and then the matching efficiency is higher than the later. This proposed method reduces the complexity of operation and improves real-time of image mosaic simultaneously.
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