matlab imadjust 用 opencv改写

原文：http://blog.csdn.net/yeyang911/article/details/18256393

自己测试的效果不是很好

实现函数功能

J = low_out +(high_out - low_out).* ((I - low_in)/(high_in - low_in)).^ gamma

[cpp] view plaincopyprint?

IplImage* ImageAdjust(IplImage *src, IplImage *dst,
double low_in, double high_in,
double low_out, double high_out, double gamma )
{
double low2 = low_in*255;
double high2 = high_in*255;
double bottom2 = low_out*255;
double top2 = high_out*255;
double err_in = high2 - low2;
double err_out = top2 - bottom2;
int x,y;
double val0,val1,val2;
// intensity transform
for( y = 0; y < src->height; y++) {
for (x = 0; x < src->width; x++){
val0 = ((uchar*)(src->imageData+src->widthStep*y))[x*src->nChannels];
val0 = pow((val0 - low2)/err_in,gamma)*err_out+bottom2;
if(val0>255) val0=255;
if(val0<0) val0=0;
((uchar*)(dst->imageData+dst->widthStep*y))[x*src->nChannels]=(uchar)val0;
val1 = ((uchar*)(src->imageData+src->widthStep*y))[x*src->nChannels+1];
val1 = pow((val1- low2)/err_in, gamma)*err_out+bottom2;
if(val1>255) val1=255;
if(val1<0) val1=0;
((uchar*)(dst->imageData+dst->widthStep*y))[x*src->nChannels+1]=(uchar)val1;
val2 = ((uchar*)(src->imageData + src->widthStep*y))[x*src->nChannels+2];
val2 = pow((val2-low2)/err_in,gamma)*err_out+bottom2;
if(val2>255) val2=255;
if(val2<0) val2=0; // Make sure src is in the range [low,high]
((uchar*)(dst->imageData+dst->widthStep*y))[x*src->nChannels+2]=(uchar)val2;
}
}
return 0;
}

测试代码：

[cpp] view plaincopyprint?

int main()
{
IplImage *src=cvLoadImage("d:/111.JPG",1);
CvSize a;
a.width=src->width;
a.height=src->height;
IplImage *dst = cvCreateImage(a,8,3);
ImageAdjust(src, dst,
0, 0.5,
0.5, 1, 1) ;
Mat c = dst;
imshow("ss",c);
waitKey();
return 0;
}

效果图原图

EMGU CV 版本

[csharp] view plaincopyprint?

private void imageAdjust(Image<Bgr,byte>src,Image<Bgr,byte>dst,double low_in, double high_in,
double low_out, double high_out, double gamma)
{
double low2 = low_in * 255;
double high2 = high_in * 255;
double bottom2 = low_out * 255;
double top2 = high_out * 255;
double err_in = high2 - low2;
double err_out = top2 - bottom2;
int x, y;
double val0, val1, val2;
// intensity transform
for (y = 0; y < src.Height; y++)
{
for (x = 0; x < src.Width; x++)
{
val0 = src.Data[y, x, 0];
val0 = Math.Pow((val0 - low2) / err_in, gamma) * err_out + bottom2;
if (val0 > 255) val0 = 255;
if (val0 < 0) val0 = 0;
dst.Data[y,x,0] = (byte)val0;
val1 = src.Data[y, x, 1];
val1 = Math.Pow((val1 - low2) / err_in, gamma) * err_out + bottom2;
if (val1 > 255) val1 = 255;
if (val1 < 0) val1 = 0;
dst.Data[y, x, 1] = (byte)val1;
val2 = src.Data[y, x, 2];
val2 = Math.Pow((val2 - low2) / err_in, gamma) * err_out + bottom2;
if (val2 > 255) val2 = 255;
if (val2 < 0) val2 = 0; // Make sure src is in the range [low,high]
dst.Data[y, x, 2] = (byte)val2;
}
}
}

上面的代码对于大图运行效率低，下面我写个优化版的

代码如下：

[csharp] view plaincopyprint?

private void imadjust(Image<Gray,byte> src)
{
double minV , maxV ;
int [] minP = new int[2];
int [] maxP = new int[2];
CvInvoke.MinMaxIdx(src, out minV, out maxV, minP, maxP);
Mat m = src.Mat;
m.ConvertTo(m, Emgu.CV.CvEnum.DepthType.Cv32F);
Mat n = new Mat(m.Size,Emgu.CV.CvEnum.DepthType.Cv32F,1);
MCvScalar p = new MCvScalar();
p.V0 = 1.0/(maxV-minV);
n.SetTo(p);
Mat dst = new Mat(m.Size,Emgu.CV.CvEnum.DepthType.Cv32F,1);
CvInvoke.Multiply(m, n, dst);
p.V0 = 255;
n.SetTo(p);//设置矩阵为p.V0 的值
CvInvoke.Multiply(dst, n, dst);
pictureBox1.Image = dst.ToImage<Gray, byte>().ToBitmap();// 显示到pictureBox上
}

都是采用向量化（矢量化）编程方式，效率不会差，但是我是简单实现，假设输出为最小为0 最大值为255的情况，且gamma 为1时的情况

如果需要别的情形需要自己根据情况编写。

这是另一个版本，只能灰度图：

参考：http://stackoverflow.com/questions/31647274/is-there-any-function-equivalent-to-matlabs-imadjust-in-opencv-with-c

网页还有一个别的，可以测试一下

#include <opencv2/opencv.hpp>
#include <vector>
using namespace std;
using namespace cv;
/*
  src and dst are grayscale, 8-bit images;
  Default input value:
           [low, high] = [0,1];  X-Direction
           [bottom, top] = [0,1]; Y-Direction
           gamma ;
  if adjust successfully, return 0, otherwise, return non-zero.
*/
#include <algorithm>
using namespace std;
using namespace cv;
void imadjust(const Mat1b& src, Mat1b& dst, int tol = 1, Vec2i in = Vec2i(0, 255), Vec2i out = Vec2i(0, 255))
{    // src : input CV_8UC1 image
    // dst : output CV_8UC1 imge
    // tol : tolerance, from 0 to 100.
    // in  : src image bounds
    // out : dst image buonds
    dst = src.clone();
    tol = max(0, min(100, tol));
    if (tol > 0)
    {        // Compute in and out limits
        // Histogram
        vector<int> hist(256, 0);
        for (int r = 0; r < src.rows; ++r) {            for (int c = 0; c < src.cols; ++c) {                hist[src(r,c)]++;
            }
        }
        // Cumulative histogram
        vector<int> cum = hist;
        for (int i = 1; i < hist.size(); ++i) {            cum[i] = cum[i - 1] + hist[i];
        }
        // Compute bounds
        int total = src.rows * src.cols;
        int low_bound = total * tol / 100;
        int upp_bound = total * (100-tol) / 100;
        in[0] = distance(cum.begin(), lower_bound(cum.begin(), cum.end(), low_bound));
        in[1] = distance(cum.begin(), lower_bound(cum.begin(), cum.end(), upp_bound));
    }
    // Stretching
    float scale = float(out[1] - out[0]) / float(in[1] - in[0]);
    for (int r = 0; r < dst.rows; ++r)
    {        for (int c = 0; c < dst.cols; ++c)
        {            int vs = max(src(r, c) - in[0], 0);
            int vd = min(int(vs * scale + 0.5f) + out[0], out[1]);
            dst(r, c) = saturate_cast<uchar>(vd);
        }
    }
}
int main()
{    Mat3b img = imread("fish.png");
    Mat1b gray;
    cvtColor(img, gray, COLOR_RGB2GRAY);
    Mat1b adjusted;
    imadjust(gray, adjusted);
    imshow("ss",adjusted);
       waitKey();
    // int low_in, high_in, low_out, high_out
    // imadjust(gray, adjusted, 0, Vec2i(low_in, high_in), Vec2i(low_out, high_out));
    return 0;
}
//int main111( int argc, char** argv )
//{//    IplImage *src=cvLoadImage("fish.png",1);
//       CvSize a;
//       a.width=src->width;
//       a.height=src->height;
//       IplImage *dst = cvCreateImage(a,8,3);
//       ImageAdjust(src, dst,
//             0, 0.5,
//             0.5, 1, 1)  ;
//       Mat gray_image = cvarrToMat(dst);
//       imshow("ss",gray_image);
//       waitKey();
//    return 0;
//}

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