ColorMaps in OpenCV#

Detailed Description#

The human perception isn’t built for observing fine changes in grayscale images. Human eyes are more sensitive to observing changes between colors, so you often need to recolor your grayscale images to get a clue about them. OpenCV now comes with various colormaps to enhance the visualization in your computer vision application.

In OpenCV you only need applyColorMap to apply a colormap on a given image. The following sample code reads the path to an image from command line, applies a Jet colormap on it and shows the result:

#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
using namespace cv;

#include <iostream>
using namespace std;

int main(int argc, const char *argv[])
{
    // We need an input image. (can be grayscale or color)
    if (argc < 2)
    {
        cerr << "We need an image to process here. Please run: colorMap [path_to_image]" << endl;
        return -1;
    }
    Mat img_in = imread(argv[1]);
    if(img_in.empty())
    {
        cerr << "Sample image (" << argv[1] << ") is empty. Please adjust your path, so it points to a valid input image!" << endl;
        return -1;
    }
    // Holds the colormap version of the image:
    Mat img_color;
    // Apply the colormap:
    applyColorMap(img_in, img_color, COLORMAP_JET);
    // Show the result:
    imshow("colorMap", img_color);
    waitKey(0);
    return 0;
}

Enumerations#

enum cv::ColormapTypes {
    cv::COLORMAP_AUTUMN = 0,
    cv::COLORMAP_BONE = 1,
    cv::COLORMAP_JET = 2,
    cv::COLORMAP_WINTER = 3,
    cv::COLORMAP_RAINBOW = 4,
    cv::COLORMAP_OCEAN = 5,
    cv::COLORMAP_SUMMER = 6,
    cv::COLORMAP_SPRING = 7,
    cv::COLORMAP_COOL = 8,
    cv::COLORMAP_HSV = 9,
    cv::COLORMAP_PINK = 10,
    cv::COLORMAP_HOT = 11,
    cv::COLORMAP_PARULA = 12,
    cv::COLORMAP_MAGMA = 13,
    cv::COLORMAP_INFERNO = 14,
    cv::COLORMAP_PLASMA = 15,
    cv::COLORMAP_VIRIDIS = 16,
    cv::COLORMAP_CIVIDIS = 17,
    cv::COLORMAP_TWILIGHT = 18,
    cv::COLORMAP_TWILIGHT_SHIFTED = 19,
    cv::COLORMAP_TURBO = 20,
    cv::COLORMAP_DEEPGREEN = 21
}

GNU Octave/MATLAB equivalent colormaps. View details

Enumeration Type Documentation#

ColormapTypes#

enum cv::ColormapTypes

#include <opencv2/imgproc.hpp>

GNU Octave/MATLAB equivalent colormaps.

Enumerator:

`COLORMAP_AUTUMN` Python: `cv.COLORMAP_AUTUMN`
`COLORMAP_BONE` Python: `cv.COLORMAP_BONE`
`COLORMAP_JET` Python: `cv.COLORMAP_JET`
`COLORMAP_WINTER` Python: `cv.COLORMAP_WINTER`
`COLORMAP_RAINBOW` Python: `cv.COLORMAP_RAINBOW`
`COLORMAP_OCEAN` Python: `cv.COLORMAP_OCEAN`
`COLORMAP_SUMMER` Python: `cv.COLORMAP_SUMMER`
`COLORMAP_SPRING` Python: `cv.COLORMAP_SPRING`
`COLORMAP_COOL` Python: `cv.COLORMAP_COOL`
`COLORMAP_HSV` Python: `cv.COLORMAP_HSV`
`COLORMAP_PINK` Python: `cv.COLORMAP_PINK`
`COLORMAP_HOT` Python: `cv.COLORMAP_HOT`
`COLORMAP_PARULA` Python: `cv.COLORMAP_PARULA`
`COLORMAP_MAGMA` Python: `cv.COLORMAP_MAGMA`
`COLORMAP_INFERNO` Python: `cv.COLORMAP_INFERNO`
`COLORMAP_PLASMA` Python: `cv.COLORMAP_PLASMA`
`COLORMAP_VIRIDIS` Python: `cv.COLORMAP_VIRIDIS`
`COLORMAP_CIVIDIS` Python: `cv.COLORMAP_CIVIDIS`
`COLORMAP_TWILIGHT` Python: `cv.COLORMAP_TWILIGHT`
`COLORMAP_TWILIGHT_SHIFTED` Python: `cv.COLORMAP_TWILIGHT_SHIFTED`
`COLORMAP_TURBO` Python: `cv.COLORMAP_TURBO`
`COLORMAP_DEEPGREEN` Python: `cv.COLORMAP_DEEPGREEN`

Function Documentation#

applyColorMap()#

void cv::applyColorMap(
InputArray src,
OutputArray dst,
InputArray userColor )

#include <opencv2/imgproc.hpp>

Python:

cv.applyColorMap(src, colormap[, dst]) -> dst

cv.applyColorMap(src, userColor[, dst]) -> dst

Applies a user colormap on a given image.

Parameters

src — The source image, grayscale or colored of type CV_8UC1 or CV_8UC3. If CV_8UC3, then the CV_8UC1 image is generated internally using cv::COLOR_BGR2GRAY.
dst — The result is the colormapped source image of the same number of channels as userColor. Note: Mat::create is called on dst.
userColor — The colormap to apply of type CV_8UC1 or CV_8UC3 and size 256

applyColorMap()#

void cv::applyColorMap(
InputArray src,
OutputArray dst,
int colormap )

#include <opencv2/imgproc.hpp>

Python:

cv.applyColorMap(src, colormap[, dst]) -> dst

cv.applyColorMap(src, userColor[, dst]) -> dst

Applies a GNU Octave/MATLAB equivalent colormap on a given image.

Parameters

src — The source image, grayscale or colored of type CV_8UC1 or CV_8UC3. If CV_8UC3, then the CV_8UC1 image is generated internally using cv::COLOR_BGR2GRAY.
dst — The result is the colormapped source image. Note: Mat::create is called on dst.
colormap — The colormap to apply, see ColormapTypes