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基于小波包自组织神经网络的图像数据融合
引用本文:陈宏,胡宁静. 基于小波包自组织神经网络的图像数据融合[J]. 兵工自动化, 2006, 25(1): 40-41,44
作者姓名:陈宏  胡宁静
作者单位:长沙理工大学,计算机与通信工程学院,湖南,长沙,410076;长沙理工大学,计算机与通信工程学院,湖南,长沙,410076
摘    要:基于小波包与模糊自组织特征映射神经网络的图像数据融合,将图像在小波包最优基下展开,利用小波包最优基空间、尺度定位性提高分辨率,获得更好的去噪效果;再采用具有很强聚类功能的自组织特征映射网络进行图像数据的聚类;最后通过计算图像像素点的灰度均值来得到图像数据的融合结果.

关 键 词:数据融合  小波包  最优基  神经网络  模糊聚类
文章编号:1006-1576(2006)01-0040-02
收稿时间:2005-05-07
修稿时间:2005-05-072005-08-27

Image Combination Based on Wavelet Packet and SONN
CHEN Hong,HU Ning-jing. Image Combination Based on Wavelet Packet and SONN[J]. Ordnance Industry Automation, 2006, 25(1): 40-41,44
Authors:CHEN Hong  HU Ning-jing
Abstract:The image combination method based on wavelet packet algorithm and fuzzy Self-organizing feature mapping neural network is that the image is expressed as a linear combination of the best bases of wavelet packet. The resolution ratio is improved through Best basis space and scale orientation of Wavelet packet, so as to get better denoising effect. The image data was clustered by using self-organizing feature mapping network with clustering function. Finally, the fusion result of image was gained through computing the gradation mean of pixels point of picture.
Keywords:Data fusion  Wavelet packet  Best basis  Self-organizing neural network (SONN)  Fuzzy clustering
本文献已被 CNKI 维普 万方数据 等数据库收录!
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