`imrestruct`的OpenCV Python和C++实现之间的差异

我正在用Python和C++实现MATLAB的imreconstruct.然而，对于我的测试用例，Python实现与MATLAB的输出匹配，而C++则不匹配.

以下是Python的实现:

def imReconstruct(marker: np.array, mask: np.array) -> np.array:
    """
    Naive implementation of MatLAB's imReconstruct function
    works when `mask` consists of mostly background (global minumum)
    will be slow otherwise
    """
    kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))

    # calculate the extreme values of the mask image
    min_val, max_val, _, _ = cv.minMaxLoc(mask)

    # clip the marker by global extrema of mask
    _, marker = cv.threshold(marker, min_val, max_val, cv.THRESH_TRUNC | cv.THRESH_BINARY_INV)

    while True:
        expanded = cv.dilate(marker, kernel)
        expanded = np.minimum(expanded, mask)

        # return `expanded` when the difference is small
        if np.max(np.abs(expanded - marker)) < 1e-5:
            return expanded

        # set expanded to marker and repeat
        marker = expanded


D = np.array(
      [[4.2426405, 3.6055512, 3.1622777, 3.       , 3.       ],
       [3.6055512, 2.828427 , 2.236068 , 2.       , 2.       ],
       [3.1622777, 2.236068 , 1.4142135, 1.       , 1.       ],
       [3.       , 2.       , 1.       , 0.       , 0.       ],
       [3.       , 2.       , 1.       , 0.       , 0.       ]], dtype=float32)

imReconstruct(D-.85,D)

# output
# array([[3.3926406, 3.3926406, 3.1622777, 3.       , 3.       ],
#        [3.3926406, 2.828427 , 2.236068 , 2.       , 2.       ],
#        [3.1622777, 2.236068 , 1.4142135, 1.       , 1.       ],
#        [3.       , 2.       , 1.       , 0.       , 0.       ],
#        [3.       , 2.       , 1.       , 0.       , 0.       ]], dtype=float32)

而C++:

Mat imReconstruct(Mat marker, Mat mask){
    /**************
     * naive implementation of MatLAB's imReconstruct
     * works when `mask` consist of mostly background (global minimum)
     * will be slow otherwise
     *************/
    Mat kernel = getStructuringElement(MORPH_RECT, Size(3,3));

    // calculate the min and max values from mask
    double minMask, maxMask;
    minMaxLoc(mask, &minMask, &maxMask);

    // clip the marker by global extrema of mask
    threshold(marker, marker, minMask, maxMask, THRESH_TRUNC|THRESH_BINARY_INV);

    Mat expanded;

    // keep filling the holes with `dilate`
    // until there are no more changes
    while (1){
        dilate(marker, expanded, kernel);
        expanded = min(expanded, mask);

        // compute the max difference
        minMaxLoc(expanded-marker, &minMask, &maxMask);

        // return image when changes are small
        if (maxMask<1e-5) return expanded;

        // set expanded as marker and continue looping
        marker = expanded;
    }
}

// test case
cv::Mat D = (cv::Mat_<float> (5,5) <<
       4.2426405, 3.6055512, 3.1622777, 3.       , 3.       ,
       3.6055512, 2.828427 , 2.236068 , 2.       , 2.       ,
       3.1622777, 2.236068 , 1.4142135, 1.       , 1.       ,
       3.       , 2.       , 1.       , 0.       , 0.       ,
       3.       , 2.       , 1.       , 0.       , 0.       
);

std::cout << imReconstruct(D - .85, D) << std::endl;

// output
// [3.3926406, 3.3926406, 3.1622777, 2.7555513, 2.3122778;
//  3.3926406, 2.8284271, 2.236068, 2, 2;
//  3.1622777, 2.236068, 1.4142135, 1, 1;
//  2.7555513, 2, 1, 0, 0;
//  2.3122778, 2, 1, 0, 0]

造成这种差异的原因是什么？我可能忽略了一些简单的事情，但我已经花了几个小时徒劳，没有任何积极的结果.