OpenCV中的本地规范化 [英] Local normalization in OpenCV

问题描述

我想在OpenCV中实现一个局部归一化算法，以减少图像中的照明差异。我找到了一个 MATLAB函数，我已在OpenCV中实现它。但是，我得到的结果不同于MATLAB函数给出的结果。

I'm trying to implement in OpenCV a local normalization algorithm to reduce the difference of illumination in an image. I have found a MATLAB function, and I have implemented it in OpenCV. However, the result that I get is different from the one given by the MATLAB function.

这是我的代码：

Mat localNorm(Mat image, float sigma1, float sigma2)
{
    Mat floatGray, blurred1, blurred2, temp1, temp2, res;

    image.convertTo(floatGray, CV_32FC1);
    floatGray = floatGray/255.0;

    int blur1 = 2*ceil(-NormInv(0.05, 0, sigma1))+1;
    cv::GaussianBlur(floatGray, blurred1, cv::Size(blur1,blur1), sigma1);
    temp1 = floatGray-blurred1;

    cv::pow(temp1, 2.0, temp2);
    int blur2 = 2*ceil(-NormInv(0.05, 0, sigma2))+1;
    cv::GaussianBlur(temp2, blurred2, cv::Size(blur2,blur2), sigma2);
    cv::pow(blurred2, 0.5, temp2);

    floatGray = temp1/temp2;
    floatGray = 255.0*floatGray;
    floatGray.convertTo(res, CV_8UC1);

    return res;
}

函数 NormInv 是Euan Dean在 this post 。

The function NormInv is the C++ implementation given by Euan Dean in this post.

下面显示了我获得的结果和理论结果，对于 sigma1 和 sigma2 （分别为2.0和20.0）

The following shows the result that I am getting and the theoretical result, for the same values of sigma1 and sigma2 (2.0 and 20.0, respectively)

我尝试对 sigma1 和 sigma2 使用不同的值，但它们都不起作用。我也尝试在高斯函数 blur1 = 0 和 blur2 = 0 ，但它也不工作。

I have tried using different values for sigma1 and sigma2, but none of them seem to work. I have also tried doing blur1=0 and blur2=0 in the Gaussian function but it doesn't work either.

任何帮助将不胜感激。提前感谢。

Any help would be appreciated. Thanks in advance.

推荐答案

您需要在0到255之间将图像标准化，然后再将其转换为CV_8UC1

you need to normalize the image between 0 and 255 before converting it to CV_8UC1

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