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基于小波变换的小目标检测
引用本文:李利荣,张桂林.基于小波变换的小目标检测[J].兵工自动化,2004,23(6):67-69.
作者姓名:李利荣  张桂林
作者单位:华中科技大学,智能控制与模式识别研究所,湖北,武汉,430071
摘    要:利用小波分析的多分辨率特性和时频局部窗特性能够克服传统方法的局限,实现小目标的精确定位检测.基于小波变换的小目标检测,先利用改进的小波变换选择合理的小波基和小波变换窗口对小目标图像滤波,后结合直方图阈值分割法分割阈值.实验结果表明该方法不仅能很好保存小目标的形状特征,还能将背景几乎完全消除.

关 键 词:小目标检测  小波变换  小波滤波  阈值分割  小波变换  小目标检测  Wavelet  Transform  Based  Target  Detection  完全  背景  形状特征  保存  结果  实验  分割阈值  阈值分割法  直方图  结合  图像滤波  窗口  小波基  选择  改进
文章编号:1006-1576(2004)06-0067-03
修稿时间:2004年5月13日

Small Target Detection Based on Wavelet Transform
LI Li-rong,ZHANG Gui-lin.Small Target Detection Based on Wavelet Transform[J].Ordnance Industry Automation,2004,23(6):67-69.
Authors:LI Li-rong  ZHANG Gui-lin
Abstract:The shortcomings of the traditional methods are overcome and the precision localization of the small target detection is realized with wavelet multi-resolution analysis and time-frequency local window analysis. The small target detection based on wavelet transform is that reasonable wavelet basis and wavelet transform window is selected with improved wavelet transform to filter small target image, and threshold is segmented combining histogram threshold segmentation. Experimental result shows the small target detection method not only can save shape character of small target but also can eliminate background color completely.
Keywords:Small target detection  Wavelet transform  Filter  Threshold segmentation
本文献已被 CNKI 维普 万方数据 等数据库收录!
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