Description: 基于MRF的图像分割，包括ICM算法，能量函数-MRF-based image segmentation, including the ICM algorithm, the energy function Platform: |
Size: 61440 |
Author:林芬华 |
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Description: 用CRF进行图像分割与检测,MATLAB编写,非常好用-With CRF for image segmentation and testing, MATLAB prepared, very easy to use Platform: |
Size: 143360 |
Author:yang junli |
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Description: 基于马尔科夫随机过程框架下的彩色图像分割，代码完整，非常值得参考。-Markov random process based on the framework of color image segmentation, code complete, very good reference. Platform: |
Size: 5581824 |
Author:gillyamylee |
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Description: 针对合成孔径雷达(SAR) 图像含有大量斑点噪声的特点,基于Contourlet 的多尺度、局部化、方向性和各向
异性等优点,并结合隐马尔科夫树( HMT) 模型和隐马尔科夫场(MRF) ,提出了一种基于Contourlet 域持续性和聚
集性的SAR 图像模糊融合分割算法。该算法有效捕获了Contourlet 子带的持续性和聚集性,并分别用HMT 和
MRF 来刻画,再依据模糊测度,将多尺度HMT 和MRF 有机融合,建立Contourlet 域HMT2MRF 融合模型,并导
出新模型下的最大后验概率(MAP) 分割公式。对实测SAR 图像进行了仿真,仿真结果和分析表明:与小波域上的
HMT2MRF 融合分割及Contourlet 域上HMT 和MRF 分割算法相比,该算法在抑制斑点噪声的同时,有效地提高
了SAR 图像的分割精度- In view of the speckle noise in the synthetic aperture radar (SAR) images , and based on the Contourlet′s
advantages of multiscale , localization , directionality , and anisot ropy , a new SAR image fusion segmentation
algorithm based on the pe rsis tence and clustering in the Contourlet domain is p roposed. The algorithm captures the
pe rsis tence and clus tering of the Contourlet t ransform , which is modeled by hidden Markov t ree (HMT) and Markov
random field (MRF) , respectively. Then , these two models are fused by fuzzy logic , resulting in a Contourlet
domain HMT2MRF fusion model . Finally , the maximum a poste rior (MAP) segmentation equation for the new fusion
model is deduced. The algorithm is used to emulate the real SAR images . Simulation results and analysis indicate that
the p roposed algorithm effectively reduces the influence of multiplicative speckle noise , imp roves the segmentation
accuracy and p rovides a bet te r visual quality for SAR images ove r the Platform: |
Size: 897024 |
Author:周二牛 |
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Description: This the sample implementation of a Markov random field (MRF) based
image segmentation algorithm-This is the sample implementation of a Markov random field (MRF) based
image segmentation algorithm Platform: |
Size: 7738368 |
Author:mike |
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Description: 基于变权重MRF的图像分割算法，特征场是使用混合高斯模型，标记场使用Pott模型，基于迭代条件模式进行分割-MRF based on weighted image segmentation algorithm, feature field is the use of Gaussian mixture model, using the tag field Pott model segmentation based on iterative model conditions Platform: |
Size: 84992 |
Author:马志远 |
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Description: 基于多尺度MRF模型的图像分割算法。使用提升小波对原始图像进行分解，使用ICM算法进行分割处理-Multi-scale MRF model based image segmentation algorithm. The original image using lifting wavelet decomposition, the use of ICM segmentation algorithm Platform: |
Size: 86016 |
Author:马志远 |
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Description: a Markov random field (MRF)
based color image segmentation algorithm-This is the sample implementation of a Markov random field (MRF)
based color image segmentation algorithm. The main code (colormrf.cpp)
has been written by Mihaly Gara (gara@inf.u-szeged.hu,
http://www.inf.u-szeged.hu/~gara/) with some minor contributions from
Zoltan Kato (kato@inf.u-szeged.hu, http://www.inf.u-szeged.hu/~kato/)
using the intenisty-based segmentation code of Csaba Gradwohl. Platform: |
Size: 21867520 |
Author:dreamer |
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Description: 基于马尔可夫随机场（MRF）的图像分割算法-Image segmentation algorithm based on Markov Random Field (MRF) Platform: |
Size: 160768 |
Author:lianxiaojie |
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Description: 提出了一种基于非下采样 Contourlet变换 ( NSCT)和马尔科夫随机场 (MRF)相结合的纹理图像分割算法。算法包括两
个步骤, 首先通过 NSCT实现对图像纹理特征的提取, 并使用模糊 C-均值完成对图像的初始分割 然后将初始分割结果用 MRF模型
表示, 通过贝叶斯置信传播得到图像的最终分割结果。实验结果表明, 对于纹理图像,该方法在分割错误率、 区域一致性以及边缘的
准确性方面都比传统小波变换的方法有了明显的改善。-A tex ture i m age seg m entation a l go rithm based on comb i nati on of non-down sa m pling Contourlet transfor m ( NSCT) andM arkov
rando m fi e l d model is proposed . The algorithm consists o f t wo steps . F ir st , the tex t u re f ea t ure of i m ag e is ex trac ted by NS CT, and the i m age
is seg m ented i n itia lly by fuzzy c- m eans Second , the pr i m aril y seg m ented results are expressed byMRF mode, l and the fi nal seg m entati on re-
s u lts are ga i ned v i a Bayes beli e f propag ati on . The exper i menta l resu lts show tha t this a l gor it hm is effecti ve fo r tex t ure i m age , it prov i desm uch
better res u lts i n erro r ra te o f segm enta tion , reg ion ho m ogene ity and edge accuracy than tho se of trad iti onal w ave let transf o r m ing m ethods Platform: |
Size: 216064 |
Author:jjdjjf |
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Description: 基于马尔科夫随机场的SAR图像分割方法，对应于采用最大后验概率准则对SAR目标切片图像分割，采用聚类分析算法求解。-SAR image segmentation based on Markov random fields, which corresponds to using the maximum posterior probability criteria for SAR Target Chip Image segmentation using cluster analysis algorithm for Platform: |
Size: 19456 |
Author:赵燕 |
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Search - mrf based segmentation