Intensity enhancement for shadow tonal range in an Image

Hello Everyone:
I am writing a C++ GUI application using Qt C++ and opencv. The program basically does post processing of image.

I n a specific function I am trying to increase the intensity of pixels falling in the Shadow tonal range. I’ve defined intensity of shadow tonal range as (25, 80). I am using a slider widget to get user input for value to be added to the existing intensity (that fall within the shadow range). I am converting the image to HSV format. Intensity modification is applied to channel[2}.
When I plot the histogram of the modified image, I see huge spikes in histogram and also gaps . I am not sure why this is happening.

Please find below the code

void changeShadow(int value)
    cv::Mat hsvImage;
    cv::Mat mergedImage;

    // HSV
    cv::cvtColor(im_processed, hsvImage, cv::COLOR_BGR2HSV);

    // Compute Luminance Histogram
    std::vector<cv::Mat> channels;
    cv::split(hsvImage, channels);

    int intensityMin = SHADOWMIN;
    int intensityMax = SHADOWMAX;
    // Get the channel 3 (value) from the split channels
    Mat channel3 = channels[2];

    // Get the number of rows and columns in the image
    int rows = hsvImage.rows;
    int cols = hsvImage.cols;

    for (int y = 0; y < rows; y++)
        for (int x = 0; x < cols; x++) {
            uchar intensity =<uchar>(y, x);
            if (intensity >= intensityMin && intensity <= intensityMax)
      <uchar>(y, x) =<uchar>(y, x) + value;
    channels[2] = channel3;
    // Normalize the image to 8-bit representation
    cv::normalize(mergedImage, mergedImage, 0, 255, cv::NORM_MINMAX, CV_8U);
    cv::cvtColor(mergedImage,im_processed, cv::COLOR_HSV2BGR );


hi, it’s unclear, what you expect to happen, can you explain ?
are there any sources / papers / links for this idea ?

I basically trying to increase the intensity in certain areas of the image (especially in areas where the intensity is between 25 and 80. I expect to see a change in shape of the histogram on the left side. However not spikes or gaps.

if you have things to show, show them. that includes histograms.