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自适应权值立体匹配算法

于 2020-09-22 发布文件大小:231KB

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下载积分: 1 下载次数: 15

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代码说明：

一种改进的自适应权值立体匹配算法，用于图像处理等(An improved adaptive weight stereo matching algorithm for image processing, etc.)

文件列表：

IterativeAveragingFilter.m, 827 , 2009-07-08
Readme.txt, 1148 , 2008-12-16
stereoGlobalEnergyMinV2.m, 6029 , 2011-06-06
stereoRegionGrowingLine.m, 7484 , 2011-06-06
view1m.png, 114953 , 2008-12-01
view5m.png, 114308 , 2008-12-01
windowSSE.m, 675 , 2011-04-25
license.txt, 1314 , 2014-02-12

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matllab_tips
First keep in mind that this is not a Matlab tutorial. This is just a list of tricks I have found useful while writing the toolboxes available on the Matlab Central repository.

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包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波(ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation: Kalman filter Extended Kalman filter Sigma-Point Kalman filters (SPKF) Unscented Kalman filter (UKF) Central difference Kalman filter (CDKF) Square-root SPKFs Gaussian mixture SPKFs Iterated SPKF SPKF smoothers Particle filters Generic SIR particle filter Gaussian sum particle filter Sigma-point particle filter Gaussian mixture sigma-point particle filter Rao-Blackwellized particle filters The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a). )

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自适应权值立体匹配算法

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