当前位置: X-MOL 学术J. Electron. Imaging › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Establishing a large amount of point correspondences using patch-based affine-scale invariant feature transform for fisheye images
Journal of Electronic Imaging ( IF 1.1 ) Pub Date : 2021-08-01 , DOI: 10.1117/1.jei.30.4.043022
Yakun Zhang 1 , Haibin Li 1 , Wenming Zhang 1
Affiliation  

Affine-scale invariant feature transform (ASIFT) has performed very well for perspective images, but the intrinsic nonlinear distortion makes it difficult to utilize ASIFT directly for fisheye images to find a large amount of correspondences. We reuse ASIFT and propose a new feature matching method for uncorrected fisheye images. First, we employ the Gaussian hemi-image to divide fisheye images into patches. In this process, we introduce Plücker coordinates and side operator to establish the correspondences between the hemispherical projection model, Gaussian hemi-image, and fisheye images. Simultaneously, maximum stable extreme region algorithm is used to detect the target regions. After that, each patch in these regions is simulated at different orientation parameters in ASIFT, and SIFT algorithm is applied to all simulated patches. Experiments on real-world images show that the proposed method can achieve good performance: the numbers of the point correspondences increase greatly with satisfactory accuracy, reliability, and efficiency.

中文翻译:

使用基于补丁的仿射尺度不变特征变换为鱼眼图像建立大量点对应关系

仿射尺度不变特征变换(ASIFT)在透视图像上表现非常好,但是内在的非线性失真使得很难直接对鱼眼图像使用 ASIFT 来找到大量的对应关系。我们重用 ASIFT 并为未校正的鱼眼图像提出了一种新的特征匹配方法。首先,我们使用高斯半图像将鱼眼图像划分为补丁。在这个过程中,我们引入了 Plücker 坐标和边算子来建立半球投影模型、高斯半图像和鱼眼图像之间的对应关系。同时采用最大稳定极值区域算法检测目标区域。之后,在ASIFT中以不同的方向参数模拟这些区域中的每个补丁,并对所有模拟补丁应用SIFT算法。
更新日期:2021-08-24
down
wechat
bug