blocks|key|372931|text|我实现了BGRA图像的直方图均衡化。我认为这个函数对你的目标很有用(但你应该忽略alpha通道)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|372932|Mat+equalizeBGRA(const+Mat&+img)
{
Mat+res(img.size(),+img.type());
Mat+imgB(img.size(),+CV_8UC1);
Mat+imgG(img.size(),+CV_8UC1);
Mat+imgR(img.size(),+CV_8UC1);
Vec4b+pixel;

if+(img.channels()+!=+4)
{
++++cout+<<+"ERROR:+image+input+is+not+a+BGRA+image!"+<<+endl;
++++return+Mat();
}

for+(int+r+=+0;+r+<+img.rows;+r%2B%2B)
{
++++for+(int+c+=+0;+c+<+img.cols;+c%2B%2B)
++++{
++++++++pixel+=+img.at<Vec4b>(r,+c);
++++++++imgB.at<uchar>(r,+c)+=+pixel[0];
++++++++imgG.at<uchar>(r,+c)+=+pixel[1];
++++++++imgR.at<uchar>(r,+c)+=+pixel[2];
++++}
}

equalizeHist(imgB,+imgB);
equalizeHist(imgG,+imgG);
equalizeHist(imgR,+imgR);

for+(int+r+=+0;+r+<+img.rows;+r%2B%2B)
{
++++for+(int+c+=+0;+c+<+img.cols;+c%2B%2B)
++++{
++++++++pixel+=+Vec4b(imgB.at<uchar>(r,+c),+imgG.at<uchar>(r,+c),+imgR.at<uchar>(r,+c),+img.at<Vec4b>(r,+c)[3]);
++++++++res.at<Vec4b>(r,+c)+=+pixel;
++++}
}

return+res;
}|code-block|syntax|javascript|372933|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I implemented a histogram equalization for BGRA image. I think this function is useful for your goal (but you should ignore the alpha channel).

<pre><code>Mat equalizeBGRA(const Mat&amp; img)
{
Mat res(img.size(), img.type());
Mat imgB(img.size(), CV_8UC1);
Mat imgG(img.size(), CV_8UC1);
Mat imgR(img.size(), CV_8UC1);
Vec4b pixel;

if (img.channels() != 4)
{
 cout &lt;&lt; "ERROR: image input is not a BGRA image!" &lt;&lt; endl;
 return Mat();
}

for (int r = 0; r &lt; img.rows; r++)
{
 for (int c = 0; c &lt; img.cols; c++)
 {
 pixel = img.at&lt;Vec4b&gt;(r, c);
 imgB.at&lt;uchar&gt;(r, c) = pixel[0];
 imgG.at&lt;uchar&gt;(r, c) = pixel[1];
 imgR.at&lt;uchar&gt;(r, c) = pixel[2];
 }
}

equalizeHist(imgB, imgB);
equalizeHist(imgG, imgG);
equalizeHist(imgR, imgR);

for (int r = 0; r &lt; img.rows; r++)
{
 for (int c = 0; c &lt; img.cols; c++)
 {
 pixel = Vec4b(imgB.at&lt;uchar&gt;(r, c), imgG.at&lt;uchar&gt;(r, c), imgR.at&lt;uchar&gt;(r, c), img.at&lt;Vec4b&gt;(r, c)[3]);
 res.at&lt;Vec4b&gt;(r, c) = pixel;
 }
}

return res;
}
</code></pre>

blocks|key|154975|text|python版本@sga：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|154976|import+cv2
import+os

def+hisEqulColor(img):
++++ycrcb=cv2.cvtColor(img,cv2.COLOR_BGR2YCR_CB)
++++channels=cv2.split(ycrcb)
++++print+len(channels)
++++cv2.equalizeHist(channels[0],channels[0])
++++cv2.merge(channels,ycrcb)
++++cv2.cvtColor(ycrcb,cv2.COLOR_YCR_CB2BGR,img)
++++return+img


fname='./your.jpg'
img=cv2.imread(fname)

cv2.imshow('img',+img)
img2=hisEqulColor(img)
cv2.imshow('img2',img2)|code-block|syntax|javascript|154977|然而，这将在图像中产生噪声(例如，下面的左图)|154978|📷|atomic|offset|length|154979|​|154980|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/6665b26da67fa677a3522906050ce6ea.png|imageAlt^0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|Z|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|10|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|11|8|@]|9|@$L|12|M|13|1|14]]|A|$]]|$1|N|3|O|5|6|7|15|8|@]|9|@]|A|$]]|$1|P|3|-4|5|6|7|16|8|@]|9|@]|A|$]]]|Q|$R|$5|S|T|U|A|$V|W|X|-4]]]]

And the python version, @sga:

<pre><code>import cv2
import os

def hisEqulColor(img):
 ycrcb=cv2.cvtColor(img,cv2.COLOR_BGR2YCR_CB)
 channels=cv2.split(ycrcb)
 print len(channels)
 cv2.equalizeHist(channels[0],channels[0])
 cv2.merge(channels,ycrcb)
 cv2.cvtColor(ycrcb,cv2.COLOR_YCR_CB2BGR,img)
 return img


fname='./your.jpg'
img=cv2.imread(fname)

cv2.imshow('img', img)
img2=hisEqulColor(img)
cv2.imshow('img2',img2)
</code></pre>

<h1>However this will produce noise in the image (Eg, the left image below) <a href="https://i.stack.imgur.com/M2FKS.png" rel="noreferrer"><img src="https://i.stack.imgur.com/M2FKS.png" alt="enter image description here"></a></h1>

I am trying to perform a histogram equalization using OpenCV using the following function

<pre><code>Mat Histogram::Equalization(const Mat&amp; inputImage)
{
 if(inputImage.channels() &gt;= 3)
 {
 vector&lt;Mat&gt; channels;
 split(inputImage,channels);
 Mat B,G,R;

 equalizeHist( channels[0], B );
 equalizeHist( channels[1], G );
 equalizeHist( channels[2], R );
 vector&lt;Mat&gt; combined;
 combined.push_back(B);
 combined.push_back(G);
 combined.push_back(R);
 Mat result;
 merge(combined,result);
 return result;
 }
 return Mat();
}
</code></pre>

But when I get the result, there seems to be no difference in input and output image, what am I doing wrong?

Sorry for the bad image quality, "Preprocessed" (left) is histogram equalized, you can see its same as the input (right).

<img src="https://i.stack.imgur.com/0ikLi.png" alt="enter image description here">

What did miss?

Histogram equalization not working on color image - OpenCV

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我尝试使用以下函数使用OpenCV执行直方图均衡化Mat Histogram::Equalization(const Mat& inputImage){ if(inputImage.channels() >= 3) { vector<Mat> channels; split(in...

问直方图均衡不适用于彩色图像- OpenCV
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