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Reconstuction3d
三维重建过程中常见的算法源码，效果良好，适合基础学习(3d reconstruction reconstruction)
- 2017-07-12 21:27:35下载
- 积分：1
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darkchanneldefog
基于暗通道先验理论的去雾算法，使用rgb暗通道计算大气光及透射率获得去雾图像(Since the scene radiance is usually not as bright as the atmospheric light, the image after haze removal looks dim. So we increase the exposure of J(x) for
display.)
- 2018-01-14 15:08:15下载
- 积分：1
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StereoDisparity
对双目视觉图像对进行匹配获取视差图，为后续三维重建做基础。(Binocular vision images are matched to obtain the disparity map, as a foundation for the subsequent three-dimensional reconstruction.)
- 2012-05-07 10:53:54下载
- 积分：1
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phasehaning
时移相位差校正法，通过时移，进行前后两次FFT分析，利用离散频谱对应峰值谱线的相位差以求出频率和相位校正量。(Phase difference correcting method by time-shifting. Make two FFT analysis before and after the time-shifting,and make use of the phase difference of the peak spectral lines to get frequency and phase correction amount.)
- 2012-10-17 11:57:43下载
- 积分：1
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imnoise1
对一幅图片批量添加20个级别的噪声，支持添加高斯白噪声和椒盐噪声两种噪声。(Add a picture batch 20 levels of noise, two noise support the addition of white Gaussian noise and salt and pepper noise.)
- 2013-05-11 09:18:34下载
- 积分：1
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butterlowfilter
巴特沃斯低通滤波器的C语言实现原理以及程序，对理解滤波器原理有很好的帮助(Butterworth low-pass filter, and a program in C language implementation principle for understanding the principles of good help filter)
- 2014-11-10 10:01:49下载
- 积分：1
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NR
说明： 基于邻域的比例算法求两幅图像的差异图，用于变化检测。(The proportion of neighborhood-based algorithms to find the difference of the two images map for change detection.)
- 2013-04-14 11:19:19下载
- 积分：1
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shujuchuli
文档介绍了大量离散实验数据的平滑滤波处理方法(Document describes a large number of discrete experimental data smoothing filter processing method)
- 2013-10-20 22:03:53下载
- 积分：1
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flooding
无线传感器网络，泛洪算法。每一轮次每个节点向中心节点发送数据。最后的生成图像为节点的死亡数。(Wireless sensor networks, the flooding algorithm. Each round, each node sends data to the central node. The final generated image is the node numbers of death.)
- 2012-07-07 18:40:48下载
- 积分：1
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covariance-tracking
该代码用于实现视觉目标跟踪研究中的协方差跟踪，能够把多种时空特征融合于统一的模型中，在实现视觉目标跟踪时具有较好的鲁棒性，而且其维数等于使用特征的数量，与各个特征的维数无关，因此，其计算复杂度较小，实时性较好。(This code is used to realize covariance tracking in the research field of visual object tracking of computer vision. It enables fusion of various spatial-temporal features into an unified object feature model, hence robust to noise. In addition, its dimension is equal to the number of the features used and independent of the dimensions of the features used. Therefore, it satisfies the requirement of real-time application due to its low computation cost.)
- 2011-07-02 06:58:54下载
- 积分：1
