convert Mat image into 2d Matrix double

edit

//code for passing 1 channel image pixel values to a 2D array

//declare ,read,convert image to 32float

    Mat img,dst;
    img=imread("IMG.JPG");
    img.convertTo(dst, CV_32F);
    float arrOut[dst.rows][dst.cols];

//pass data to 2D array

    for(int i = 0 ;i < dst.rows; ++i)
        for(int j = 0; j < dst.cols; ++j)
            arrOut[i][j]=dst.at<float>(i,j);

//show the array

    for(int i = 0 ;i < dst.rows; ++i)
        for(int j = 0; j < dst.cols; ++j)
        {  cout<<arrOut[i][j]<<" ";
           if(j==(dst.cols-1))
                  cout<<endl;
        }

When Mat is continous (bool isContinous = src.isContinous()) you can use a simple pointer. If you have a submatrix of a Mat (src(Rect(x, y, w, h)) normaly a row is continous, so you can set a pointer to the begining of a row.

cv::Mat src; // some input image
cv::Mat dst;

// Convert to double (much faster than a simple for loop)
src.convertTo(dst, CV_64F, 1, 0);

 if(dst.isContinous()) {
    double *ptrDst = dst.ptr<double>();   
    for(int i = 0; i < dst.total(); ++i) {
            double value = ptrDst[i]; // Or do some other stuff
    }
} else
    for(int i = 0 i < dst.rows; ++i) {
        double *ptrDst = dst.ptr<double>(i);

        for(int j = 0; j < dst.cols; ++j) {
            double value = ptrDst[j];
        }
    }
}

Or for 2D matrix access:

cv::Mat src; // some input image
cv::Mat dst;

// Convert to double (much faster than a simple for loop)
src.convertTo(dst, CV_64F, 1, 0);

double *ptrDst[dst.rows];
for(int i = 0 i < dst.rows; ++i) {
    ptrDst[i] = dst.ptr<double>(i);

    for(int j = 0; j < dst.cols; ++j) {
        double value = ptrDst[i][j];
    }
}

Edit: You use a 3 channel image, above example is for 1 channel image. So storage order is explained here. The data access is similar to example above with respect to the 3 channel storage.

Edit2: code corrected. Thanks to LBerger.