文件名称:work
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 2.94mb
- 下载次数：
- 0次
- 提 供 者：
- 殷**
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
针对FCM算法的运行时间长和计算量大的问题，提出了改进的FCM算法，先将图像分割成窗口大小的子块，然后以子块为单位提取特征向量，用FCM聚类粗分割，然后对边缘子块，以像素为单位从新提取特征向量，进行细分割。分割后的结果提高了运行速度和分割精度。-For the FCM algorithm and the calculation of long run the problem of large proposed improved FCM algorithm, first image into blocks the size of the window, and then sub-block feature vector extraction unit, using FCM clustering coarse partition, and then block on the edge, in pixels from the new Feature Extraction, for fine segmentation. Improve the segmentation results after the speed and accuracy of segmentation.
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下载文件列表
work\12.fig
....\1234.fig
....\13.fig
....\147.bmp
....\2.fig
....\234.asv
....\asd
....\biaozhun.bmp
....\biaozhun4.bmp
....\f2.fig
....\fc.asv
....\fc.m
....\fcm2.fig
....\fcm2.m
....\fcm3.fig
....\fcm3.m
....\fcmd.fig
....\fcmnew1.fig
....\fcmnew1.m
....\fcmnew10.fig
....\fcmnew10.m
....\fcmw.m
....\fd.asv
....\fengehoudetuxiang.fig
....\fun.asv
....\func.asv
....\func.m
....\func_DWT.asv
....\func_DWT.m
....\func_Main.asv
....\func_Main.m
....\func_Main2.asv
....\func_Main2.m
....\func_Main3.asv
....\func_Main3.m
....\func_Main4.asv
....\func_Main4.m
....\func_Mywavedec2.asv
....\func_wavelet.asv
....\func_wavelet.m
....\func_wavelet_packet.asv
....\func_wavelet_packet.m
....\hs_err_pid3804.log
....\K.asv
....\k.bmp
....\K.m
....\km2.fig
....\kmeans2.fig
....\kmeans2.m
....\kmeans3.fig
....\kmeans3.m
....\kmeans4.fig
....\kmeans4.m
....\kmeansnew0.fig
....\kmeansnew0.m
....\kmnew10.fig
....\kmnew10.m
....\kw4.fig
....\Lenna.bmp
....\lianxi.asv
....\lianxi.m
....\ll.asv
....\ll.m
....\lmi.asv
....\lmi.m
....\lmilianxi.m
....\my_syn1_result.mat
....\new0.bmp
....\new1.bmp
....\new10.jpg
....\new2.bmp
....\new2_1.bmp
....\new3.bmp
....\new4.bmp
....\new5.bmp
....\page.png
....\sar.bmp
....\tiaoshi.asv
....\tshape.png
....\Untitled.asv
....\untitled.fig
....\Untitled.m
....\Untitled2.asv
....\w4.bmp
....\wenli2.bmp
....\wenli4.bmp
....\wenlifenge.asv
....\ww.asv
....\ww.bmp
....\yf2.fig
....\yuan1.fig
....\yuankm2.fig
work
....\1234.fig
....\13.fig
....\147.bmp
....\2.fig
....\234.asv
....\asd
....\biaozhun.bmp
....\biaozhun4.bmp
....\f2.fig
....\fc.asv
....\fc.m
....\fcm2.fig
....\fcm2.m
....\fcm3.fig
....\fcm3.m
....\fcmd.fig
....\fcmnew1.fig
....\fcmnew1.m
....\fcmnew10.fig
....\fcmnew10.m
....\fcmw.m
....\fd.asv
....\fengehoudetuxiang.fig
....\fun.asv
....\func.asv
....\func.m
....\func_DWT.asv
....\func_DWT.m
....\func_Main.asv
....\func_Main.m
....\func_Main2.asv
....\func_Main2.m
....\func_Main3.asv
....\func_Main3.m
....\func_Main4.asv
....\func_Main4.m
....\func_Mywavedec2.asv
....\func_wavelet.asv
....\func_wavelet.m
....\func_wavelet_packet.asv
....\func_wavelet_packet.m
....\hs_err_pid3804.log
....\K.asv
....\k.bmp
....\K.m
....\km2.fig
....\kmeans2.fig
....\kmeans2.m
....\kmeans3.fig
....\kmeans3.m
....\kmeans4.fig
....\kmeans4.m
....\kmeansnew0.fig
....\kmeansnew0.m
....\kmnew10.fig
....\kmnew10.m
....\kw4.fig
....\Lenna.bmp
....\lianxi.asv
....\lianxi.m
....\ll.asv
....\ll.m
....\lmi.asv
....\lmi.m
....\lmilianxi.m
....\my_syn1_result.mat
....\new0.bmp
....\new1.bmp
....\new10.jpg
....\new2.bmp
....\new2_1.bmp
....\new3.bmp
....\new4.bmp
....\new5.bmp
....\page.png
....\sar.bmp
....\tiaoshi.asv
....\tshape.png
....\Untitled.asv
....\untitled.fig
....\Untitled.m
....\Untitled2.asv
....\w4.bmp
....\wenli2.bmp
....\wenli4.bmp
....\wenlifenge.asv
....\ww.asv
....\ww.bmp
....\yf2.fig
....\yuan1.fig
....\yuankm2.fig
work