c++ - OpenCV: How to visualize a depth image

Question

I am using a dataset in which it has images where each pixel is a 16 bit unsigned int storing the depth value of that pixel in mm. I am trying to visualize this as a greyscale depth image by doing the following:

cv::Mat depthImage; 
depthImage = cv::imread("coffee_mug_1_1_1_depthcrop.png", CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR ); // Read the file 
depthImage.convertTo(depthImage, CV_32F); // convert the image data to float type   
namedWindow("window");
float max = 0;
for(int i = 0; i < depthImage.rows; i++){
    for(int j = 0; j < depthImage.cols; j++){
        if(depthImage.at<float>(i,j) > max){
            max = depthImage.at<float>(i,j);
        }
    }   
}
cout << max << endl;


float divisor = max / 255.0;
cout << divisor << endl;
for(int i = 0; i < depthImage.rows; i++){
    for(int j = 0; j < depthImage.cols; j++){
        cout << depthImage.at<float>(i,j) << ", ";
        max = depthImage.at<float>(i,j) /= divisor;
        cout << depthImage.at<float>(i,j) << endl;
    }   
}


imshow("window", depthImage);
waitKey(0);

However, it is only showing two colours this is because all of the values are close together i.e. in the range of 150-175 + the small values which show up black (see below).

Is there a way to normalize this data such that it will show various grey levels to highlight these small depth differences?

Answer 1

According to the documentation, the function imshow can be used with a variety of image types. It support 16-bit unsigned images, so you can display your image using

cv::Mat map = cv::imread("image", CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH);
cv::imshow("window", map);

In this case, the image value range is mapped from the range [0, 255*256] to the range [0, 255].

If your image only contains values on the low part of this range, you will observe an obscure image. If you want to use the full display range (from black to white), you should adjust the image to cover the expected dynamic range, one way to do it is

double min;
double max;
cv::minMaxIdx(map, &min, &max);
cv::Mat adjMap;
cv::convertScaleAbs(map, adjMap, 255 / max);
cv::imshow("Out", adjMap);