opencv用户手册之图像处理部分（之四）：滤波器与色彩转换（中文翻译） - hunnish的opencv专栏.htm

Opencv的中文参考指南

        <P align=center>B</FONT></P></TD>
      <TD><FONT color=#008000 size=5>
        <P align=center>G</FONT></P></TD>
      <TD><FONT color=#0000ff size=5>
        <P align=center>B</FONT></P></TD>
      <TD><FONT color=#008000 size=5>
        <P align=center>G</FONT></P></TD></TR></TBODY></TABLE>
  <P>The output RGB components of a pixel are interpolated from 1, 2 or 4 
  neighbors of the pixel having the same color. There are several modifications 
  of the above pattern that can be achieved by shifting the pattern one pixel 
  left and/or one pixel up. The two letters C<SUB>1</SUB> and C<SUB>2</SUB> in 
  the conversion constants CV_BayerC<SUB>1</SUB>C<SUB>2</SUB>2{BGR|RGB} indicate 
  the particular pattern type - these are components from the second row, second 
  and third columns, respectively. For example, the above pattern has very 
  popular "BG" type.</P></LI></UL>
<HR>

<H3><A name=decl_cvThreshold>Threshold</A></H3>
<P class=Blurb>对数组元素进行固定阈值操作</P><PRE>void cvThreshold( const CvArr* src, CvArr* dst, double threshold,
                  double max_value, int threshold_type );
</PRE>
<P>
<DL>
  <DT>src 
  <DD>原始数组 (单通道, 8-比特 of 32-比特 浮点数). 
  <DT>dst 
  <DD>输出数组，必须与 <CODE>src</CODE> 的类型一致，或者为 8-比特. 
  <DT>threshold 
  <DD>阈值 
  <DT>max_value 
  <DD>使用 <CODE>CV_THRESH_BINARY</CODE> 和 <CODE>CV_THRESH_BINARY_INV</CODE> 的最大值. 

  <DT>threshold_type 
  <DD>阈值类型 (见讨论) </DD></DL>
<P>函数 <A 
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cv.HTM#decl_cvThreshold"><FONT 
color=#002c99>cvThreshold</FONT></A> 对单通道数组应用固定阈值操作。典型的是对灰度图像进行阈值操作得到二值图像。(<A 
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cxcore.htm#decl_cvCmpS"><FONT 
color=#002c99>cvCmpS</FONT></A> 也可以达到此目的) 
或者是去掉噪声，例如过滤很小或很大象素值的图像点。有好几种对图像取阈值的方法，本函数支持的方法由 <CODE>threshold_type 
确定</CODE>:</P><PRE>threshold_type=CV_THRESH_BINARY:
dst(x,y) = max_value, if src(x,y)&gt;threshold
           0, otherwise

threshold_type=CV_THRESH_BINARY_INV:
dst(x,y) = 0, if src(x,y)&gt;threshold
           max_value, otherwise

threshold_type=CV_THRESH_TRUNC:
dst(x,y) = threshold, if src(x,y)&gt;threshold
           src(x,y), otherwise

threshold_type=CV_THRESH_TOZERO:
dst(x,y) = src(x,y), if (x,y)&gt;threshold
           0, otherwise

threshold_type=CV_THRESH_TOZERO_INV:
dst(x,y) = 0, if src(x,y)&gt;threshold
           src(x,y), otherwise
</PRE>
<P>下面是图形化的阈值描述：</P>
<P><IMG src="" align=center> </P>
<HR>

<H3><A name=decl_cvAdaptiveThreshold>AdaptiveThreshold</A></H3>
<P class=Blurb>自适应阈值方法</P><PRE>void cvAdaptiveThreshold( const CvArr* src, CvArr* dst, double max_value,
                          int adaptive_method=CV_ADAPTIVE_THRESH_MEAN_C,
                          int threshold_type=CV_THRESH_BINARY,
                          int block_size=3, double param1=5 );
</PRE>
<P>
<DL>
  <DT>src 
  <DD>输入图像. 
  <DT>dst 
  <DD>输出图像. 
  <DT>max_value 
  <DD>使用 <CODE>CV_THRESH_BINARY</CODE> 和 <CODE>CV_THRESH_BINARY_INV</CODE> 的最大值. 

  <DT>adaptive_method 
  <DD>自适应阈值算法使用：<CODE>CV_ADAPTIVE_THRESH_MEAN_C</CODE> 或 
  <CODE>CV_ADAPTIVE_THRESH_GAUSSIAN_C</CODE> （见讨论）. 
  <DT>threshold_type 
  <DD>取阈值类型：必须是下者之一 
  <UL>
    <LI><CODE>CV_THRESH_BINARY,</CODE> 
    <LI><CODE>CV_THRESH_BINARY_INV</CODE> </LI></UL>
  <DT>block_size 
  <DD>用来计算阈值的象素邻域大小: 3, 5, 7, ... 
  <DT>param1 
  <DD>与方法有关的参数。对方法 <CODE>CV_ADAPTIVE_THRESH_MEAN_C</CODE> 和 
  <CODE>CV_ADAPTIVE_THRESH_GAUSSIAN_C</CODE>， 它是一个从均值或加权均值提取的常数（见讨论）, 尽管它可以是负数。 
  </DD></DL>
<P>函数 <A 
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cv.HTM#decl_cvAdaptiveThreshold"><FONT 
color=#002c99>cvAdaptiveThreshold</FONT></A> 将灰度图像变换到二值图像，采用下面公式：</P><PRE>threshold_type=<CODE>CV_THRESH_BINARY</CODE>:
dst(x,y) = max_value, if src(x,y)&gt;T(x,y)
           0, otherwise

threshold_type=<CODE>CV_THRESH_BINARY_INV</CODE>:
dst(x,y) = 0, if src(x,y)&gt;T(x,y)
           max_value, otherwise
</PRE>
<P>其中 T<SUB>I</SUB> 是为每一个象素点单独计算的阈值</P>
<P>对方法 CV_ADAPTIVE_THRESH_MEAN_C，它是 block_size × block_size 块中的象素点，被参数 param1 
所减，得到的均值，</P>
<P>对方法 CV_ADAPTIVE_THRESH_GAUSSIAN_C 它是 block_size × block_size 块中的象素点，被参数 
param1 所减，得到的加权和(gaussian)。</P><BR><BR>
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[<A href="javascript:StorePage()">点击此处收藏本文</A>]&nbsp;&nbsp; 发表于 2004年09月06日 
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<H3></H3><A name=291249>&nbsp;</A>
<DIV class=post>
<DIV class=postTitle>schwartz&nbsp;发表于2005-02-17 4:45 PM&nbsp;&nbsp;IP: 
202.232.87.*</DIV>
<DIV class=postText>谢谢楼主的介绍，不过色彩空间转换中反求G的公式中，Cb和Cr位置反了。</DIV></DIV><BR></DIV>
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