ColorMaps in OpenCV

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 }
	GNU Octave/MATLAB equivalent colormaps. More...

Functions
void	cv::applyColorMap (InputArray src, OutputArray dst, int colormap)
	Applies a GNU Octave/MATLAB equivalent colormap on a given image. More...
void	cv::applyColorMap (InputArray src, OutputArray dst, InputArray userColor)
	Applies a user colormap on a given image. More...

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;
}

See also

ColormapTypes

Enumeration Type Documentation

ColormapTypes

enum cv::ColormapTypes

#include <opencv2/imgproc.hpp>

GNU Octave/MATLAB equivalent colormaps.

Enumerator
COLORMAP_AUTUMN  Python: cv.COLORMAP_AUTUMN	autumn
COLORMAP_BONE  Python: cv.COLORMAP_BONE	bone
COLORMAP_JET  Python: cv.COLORMAP_JET	jet
COLORMAP_WINTER  Python: cv.COLORMAP_WINTER	winter
COLORMAP_RAINBOW  Python: cv.COLORMAP_RAINBOW	rainbow
COLORMAP_OCEAN  Python: cv.COLORMAP_OCEAN	ocean
COLORMAP_SUMMER  Python: cv.COLORMAP_SUMMER	summer
COLORMAP_SPRING  Python: cv.COLORMAP_SPRING	spring
COLORMAP_COOL  Python: cv.COLORMAP_COOL	cool
COLORMAP_HSV  Python: cv.COLORMAP_HSV	HSV
COLORMAP_PINK  Python: cv.COLORMAP_PINK	pink
COLORMAP_HOT  Python: cv.COLORMAP_HOT	hot
COLORMAP_PARULA  Python: cv.COLORMAP_PARULA	parula
COLORMAP_MAGMA  Python: cv.COLORMAP_MAGMA	magma
COLORMAP_INFERNO  Python: cv.COLORMAP_INFERNO	inferno
COLORMAP_PLASMA  Python: cv.COLORMAP_PLASMA	plasma
COLORMAP_VIRIDIS  Python: cv.COLORMAP_VIRIDIS	viridis
COLORMAP_CIVIDIS  Python: cv.COLORMAP_CIVIDIS	cividis
COLORMAP_TWILIGHT  Python: cv.COLORMAP_TWILIGHT	twilight
COLORMAP_TWILIGHT_SHIFTED  Python: cv.COLORMAP_TWILIGHT_SHIFTED	twilight shifted
COLORMAP_TURBO  Python: cv.COLORMAP_TURBO	turbo

Function Documentation

applyColorMap() [1/2]

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

Python:
	dst	=	cv.applyColorMap(	src, colormap[, dst]	)
	dst	=	cv.applyColorMap(	src, userColor[, dst]	)

#include <opencv2/imgproc.hpp>

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.
dst	The result is the colormapped source image. Note: Mat::create is called on dst.
colormap	The colormap to apply, see ColormapTypes

Examples:

samples/cpp/falsecolor.cpp.

applyColorMap() [2/2]

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

Python:
	dst	=	cv.applyColorMap(	src, colormap[, dst]	)
	dst	=	cv.applyColorMap(	src, userColor[, dst]	)

#include <opencv2/imgproc.hpp>

Applies a user colormap on a given image.

Parameters

src	The source image, grayscale or colored of type CV_8UC1 or CV_8UC3.
dst	The result is the colormapped source image. Note: Mat::create is called on dst.
userColor	The colormap to apply of type CV_8UC1 or CV_8UC3 and size 256