搜索资源列表
Harris_conner_detection
- Harris_conner_detection，用MATLAB实现Harris角点检测算子的源码，用于特征点提取及图像配准等。-Harris_conner_detection, use MATLAB to achieve Harris corner detection operator of the source code for the feature point extraction and image registration and so on.
zhiyudian-tuxiangpeizhu
- 基于点的matlab图像配准.提出一种基于小波系数的特征索引算法，实现了图像特征点对的快速搜索和两幅图像之间的匹配-Based on the point of matlab Image Registration. Presents a feature based on wavelet coefficients indexing algorithm to realize the image feature points on the fast search and matching between
1
- 本文就针对大型场景的这些特点，提出了新的基于特征的自动配准算法。-The main work of this thesis is to deal with the range data registration problem for large-scale scenes. On the basis of analysis of properties of real scenes, we propose a new automatic feature-based registration alg
Feaorithm
- 基于特征点的合成孔径雷达复图像自动配准算法-Feature points based on synthetic aperture radar complex automatic image registration algorithm
pointExtraction
- 文件中的是图像配准过程中常用的几种提取特征点的方法-Several common methods of extracting keypoits in the process of image registration
image-registration-
- 一篇很好的基于特征点的图像配准算法研究论文，很有参考意义！-A good feature points based image registration algorithm research papers, meaning a good reference!
mosaic
- matlab编写的基于特征点的图像配准的代码，希望对大家有用-matlab feature point-based image registration code, written in the hope that useful
image-mosaic
- 本文研究了两种图像配准算法:基于特征和基于变换域的图像配准算法。 在基于特征的配准算法的基础上,提出一种稳健的基于特征点的配准算法。-In this paper, two image registration algorithm: Based on the characteristics and transform domain-based image registration algorithm. In feature-based registration algorithm based on
sift
- sift特征提取算法，配准算法，匹配算法，测试通过-sift Feature extraction algorithm, registration algorithm, matching algorithm, testing through
SIF
- 基于sift的图像配准，基于抓取图像特征的方法-Based on sift image registration, based on the method of capturing image features
pj
- 图像配准的简单运行，有坐标轴，获取特征点(image registration of simple operation, coordinate axis, access to feature points)
LS
- 传统的点云配准方法，与最小二乘坐标转换相似，基于特征点的刚性变换配准方法(point cloud registration)
sift配准
- sift特征配准源代码，已经测试可以运行，有测试图片，比较好的代码