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ppbNakagami

于 2021-04-12 发布文件大小:681KB

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下载积分: 1 下载次数: 35

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代码说明：

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

文件列表：

ppbNakagami
...........\example_nakagami.m,1114,2010-03-23
...........\exemple_nakagami.m,1114,2010-03-23

...........\plotimage.m,187,2010-03-23
...........\plotimage_sar.m,326,2010-03-23
...........\ppbNakagami.mexa64,637537,2010-03-23
...........\ppbNakagami.mexglx,618644,2010-03-23
...........\ppbNakagami.mexw32,77824,2010-03-23
...........\ppbNakagami.mexw64,263168,2012-05-26
...........\ppb_nakagami.m,6853,2012-05-26
...........\psnr.m,137,2010-03-23
...........\htm" target=_blank>README,2624,2012-05-26
...........\snr.m,129,2010-03-23

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积分：1
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2008-05-20 16:07:55下载

积分：1
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针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )

2012-03-06 16:27:41下载

积分：1
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2013-11-18 15:30:26下载

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2014-05-21 19:46:11下载

积分：1
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显示处理后的BMP图像文件，VC C++ (read the bmp images )

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积分：1
Picture_recognition
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2011-06-20 10:27:31下载

积分：1

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