📄 小波变换在医学图像边缘提取中的应用.htm
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<P class=MsoNormal align=center><B><FONT face=宋体 size=5><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman">小波变换在医学图像边缘提取中的应用</SPAN><SPAN
lang=EN-US><O:P></O:P> </SPAN></FONT></B></P>
<P class=MsoNormal align=center><FONT face=宋体 size=3><B><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman">舒小华，刘耦耕</SPAN><SPAN
lang=EN-US><O:P></O:P> </SPAN></B></FONT></P>
<P class=MsoNormal align=center><SPAN lang=EN-US><B><FONT face=宋体
size=3>(</FONT></B></SPAN><B><FONT face=宋体 size=3><SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">株洲工学院</SPAN>
<SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">电气工程系湖南</SPAN>
<SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">株洲</SPAN><SPAN
lang=EN-US>412008)</SPAN></FONT></B></P>
<P class=MsoNormal><FONT face=宋体 size=3><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman"> <B>摘 要：</B>边缘是图像的重要特征。医学图像往往较模糊，其边缘特征难</SPAN><SPAN
lang=EN-US><O:P></SPAN><SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">以用传统方法检测。小波变换具有良好的局部化特性、多分辨特性，及检测信号局部突变的</SPAN><SPAN
lang=EN-US><O:P></SPAN><SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">能力。对图像进行二维小波变换，其梯度模值反映了图像的边缘。介绍一种基于小波变换的</SPAN><SPAN
lang=EN-US><O:P></SPAN><SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">图像边缘提取方法。实验证明，与传统边缘检测方法相比，该方法去噪效果好，能提取图像</SPAN><SPAN
lang=EN-US><O:P></SPAN><SPAN
style="FONT-FAMILY: 宋体; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'">中较弱的边缘，且能使边缘细化。这些特点使得他特别适合于医学图像边缘的提取。<BR> </SPAN></FONT><FONT
face=宋体 size=3><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman"><B>关键词：</B>小波变换；边缘检测；医学图像；二维小波</SPAN><SPAN
lang=EN-US><O:P></O:P> </SPAN></FONT></P>
<P class=MsoNormal align=center><SPAN lang=EN-US><FONT face=宋体
size=2><B>Application of Wavelet Transform in Edges Detection of Medi<O:P>
cal Image</B></FONT></SPAN><FONT face=宋体 size=2><B><SPAN
lang=EN-US><O:P></O:P> </SPAN></B></FONT></P>
<P class=MsoNormal align=center><FONT face=宋体 size=2><SPAN lang=EN-US>SHU
Xiaohua</SPAN><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman">，</SPAN><SPAN
lang=EN-US>LIU Ougeng<O:P></O:P> </SPAN></FONT></P>
<P class=MsoNormal align=center><SPAN lang=EN-US><FONT face=宋体
size=2>(Department of Electrical Engineering, Zhuzhou Institute of
Tec<O:P>hnology, Zhuzhou,412008, China)<O:P></O:P> </FONT></SPAN></P>
<P class=MsoNormal><FONT face=宋体 size=2><SPAN
lang=EN-US> <B>Abstract</B></SPAN><B><SPAN
style="mso-ascii-font-family: Times New Roman; mso-hansi-font-family: Times New Roman">：</SPAN></B><SPAN
lang=EN-US>The most important characteristic of image is edges<O:P>Medical
image is usually fuzzy, and its edges are difficult to detect by
tradi<O:P> tional methods</SPAN><SPAN
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