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 }
	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

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

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]	)

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]	)

Applies a user colormap on a given image.