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denoise_source
精心收集的几个去噪算法,包括基于视觉的非线性去噪、BLS_GSM算法、NL-Bayes图像去噪、KSVD去噪等,内容为核心代码,需要配置完善。
(Denoising algorithm of several carefully collected, including visual based nonlinear denoising, BLS_GSM algorithm, NL-Bayes image denoising, KSVD denoising, the content as the core code, the need to improve the allocation of.
)
- 2015-03-10 08:57:56下载
- 积分:1
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process
该程序可以对图像进行二值化处理,提取边缘点坐标。(The program can be two-valued image processing, extraction of the edge point coordinates.)
- 2020-07-08 11:28:57下载
- 积分:1
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Edge-Detection
边缘检测 Edge Detection Edge Detection(Edge Detection)
- 2014-05-08 13:49:15下载
- 积分:1
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Mirror_DImageProcess
这个实例就像一个魔镜一样,能把原始图像照出各种变换效果,是基于MFC的多文档应用程序(This example is like a mirror,which can convert original image according to a variety of effects)
- 2013-11-29 16:23:24下载
- 积分:1
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CodeMatch
视觉测量中编码点与非编码点的匹配的方法实现(Vision measuring, coding point and the coding point matching
)
- 2020-12-18 21:19:10下载
- 积分:1
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PMFFT
PMF FFT捕获技术性能仿真,分段匹配滤波法和改进算法相比较(FFT PMF capture technology performance simulation, segmented matching filter and improved algorithm comparison)
- 2021-03-08 21:29:28下载
- 积分:1
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salt-and-pepper-
halcon代码 ,对图像添加高斯噪声 椒盐噪声(halcon code, add the image Gaussian noise impulse noise)
- 2015-06-29 10:40:11下载
- 积分:1
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SIFTVC6
sift角点检测及匹配,在不同尺度空间下的角点检测方法,很方便实用。(sift corner detection and matching, the corner detection methods under different scales of space, it is convenient and practical.)
- 2013-12-08 17:25:35下载
- 积分:1
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VCPP-image-processing-chapter07
VisualC++数字图像处理技术详解第2版光盘-第七章(VisualC++ digital image processing technology Detailed Version 2 CD- Chapter VII)
- 2016-04-16 13:35:33下载
- 积分:1
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ICP-point-cloud-registration
三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准
效率较低,提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准,获得较好
的点云初始位置,然后在经典 ICP 算法的基础上,采用 k - d tree 结构实现加速搜索,并利用方向向量夹角阈值去除
错误点对,提高算法的效率。实验表明,本算法流程在保证配准精度的前提下,显著提高了配准效率。
(Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)
- 2016-08-01 10:34:57下载
- 积分:1