?? opencv用戶手冊(cè)之圖像處理部分（之四）：濾波器與色彩轉(zhuǎn)換（中文翻譯） - hunnish的opencv專(zhuān)欄.htm
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<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>對(duì)數(shù)組元素進(jìn)行固定閾值操作</P><PRE>void cvThreshold( const CvArr* src, CvArr* dst, double threshold,
double max_value, int threshold_type );
</PRE>
<P>
<DL>
<DT>src
<DD>原始數(shù)組 (單通道, 8-比特 of 32-比特 浮點(diǎn)數(shù)).
<DT>dst
<DD>輸出數(shù)組，必須與 <CODE>src</CODE> 的類(lèi)型一致，或者為 8-比特.
<DT>threshold
<DD>閾值
<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>閾值類(lèi)型 (見(jiàn)討論) </DD></DL>
<P>函數(shù) <A
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cv.HTM#decl_cvThreshold"><FONT
color=#002c99>cvThreshold</FONT></A> 對(duì)單通道數(shù)組應(yīng)用固定閾值操作。典型的是對(duì)灰度圖像進(jìn)行閾值操作得到二值圖像。(<A
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cxcore.htm#decl_cvCmpS"><FONT
color=#002c99>cvCmpS</FONT></A> 也可以達(dá)到此目的)
或者是去掉噪聲，例如過(guò)濾很小或很大象素值的圖像點(diǎn)。有好幾種對(duì)圖像取閾值的方法，本函數(shù)支持的方法由 <CODE>threshold_type
確定</CODE>:</P><PRE>threshold_type=CV_THRESH_BINARY:
dst(x,y) = max_value, if src(x,y)>threshold
0, otherwise
threshold_type=CV_THRESH_BINARY_INV:
dst(x,y) = 0, if src(x,y)>threshold
max_value, otherwise
threshold_type=CV_THRESH_TRUNC:
dst(x,y) = threshold, if src(x,y)>threshold
src(x,y), otherwise
threshold_type=CV_THRESH_TOZERO:
dst(x,y) = src(x,y), if (x,y)>threshold
0, otherwise
threshold_type=CV_THRESH_TOZERO_INV:
dst(x,y) = 0, if src(x,y)>threshold
src(x,y), otherwise
</PRE>
<P>下面是圖形化的閾值描述：</P>
<P><IMG src="" align=center> </P>
<HR>
<H3><A name=decl_cvAdaptiveThreshold>AdaptiveThreshold</A></H3>
<P class=Blurb>自適應(yīng)閾值方法</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>輸入圖像.
<DT>dst
<DD>輸出圖像.
<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>自適應(yīng)閾值算法使用：<CODE>CV_ADAPTIVE_THRESH_MEAN_C</CODE> 或
<CODE>CV_ADAPTIVE_THRESH_GAUSSIAN_C</CODE> （見(jiàn)討論）.
<DT>threshold_type
<DD>取閾值類(lèi)型：必須是下者之一
<UL>
<LI><CODE>CV_THRESH_BINARY,</CODE>
<LI><CODE>CV_THRESH_BINARY_INV</CODE> </LI></UL>
<DT>block_size
<DD>用來(lái)計(jì)算閾值的象素鄰域大小: 3, 5, 7, ...
<DT>param1
<DD>與方法有關(guān)的參數(shù)。對(duì)方法 <CODE>CV_ADAPTIVE_THRESH_MEAN_C</CODE> 和
<CODE>CV_ADAPTIVE_THRESH_GAUSSIAN_C</CODE>， 它是一個(gè)從均值或加權(quán)均值提取的常數(shù)（見(jiàn)討論）, 盡管它可以是負(fù)數(shù)。
</DD></DL>
<P>函數(shù) <A
href="file:///D:/程序/OpenCV/docs/ref/opencvref_cv.HTM#decl_cvAdaptiveThreshold"><FONT
color=#002c99>cvAdaptiveThreshold</FONT></A> 將灰度圖像變換到二值圖像，采用下面公式：</P><PRE>threshold_type=<CODE>CV_THRESH_BINARY</CODE>:
dst(x,y) = max_value, if src(x,y)>T(x,y)
0, otherwise
threshold_type=<CODE>CV_THRESH_BINARY_INV</CODE>:
dst(x,y) = 0, if src(x,y)>T(x,y)
max_value, otherwise
</PRE>
<P>其中 T<SUB>I</SUB> 是為每一個(gè)象素點(diǎn)單獨(dú)計(jì)算的閾值</P>
<P>對(duì)方法 CV_ADAPTIVE_THRESH_MEAN_C，它是 block_size × block_size 塊中的象素點(diǎn)，被參數(shù) param1
所減，得到的均值，</P>
<P>對(duì)方法 CV_ADAPTIVE_THRESH_GAUSSIAN_C 它是 block_size × block_size 塊中的象素點(diǎn)，被參數(shù)
param1 所減，得到的加權(quán)和(gaussian)。</P><BR><BR>
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[<A href="javascript:StorePage()">點(diǎn)擊此處收藏本文</A>] 發(fā)表于 2004年09月06日
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<DIV class=postTitle>schwartz 發(fā)表于2005-02-17 4:45 PM IP:
202.232.87.*</DIV>
<DIV class=postText>謝謝樓主的介紹，不過(guò)色彩空間轉(zhuǎn)換中反求G的公式中，Cb和Cr位置反了。</DIV></DIV><BR></DIV>
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