how to convert a gray scale image to color image using matlab

Question

learningmat 2013-9-11

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评论： Image Analyst 2023-4-2

Hi all, Is there any possibility to convert ab gray scale image into color image.If so, kindly suggest me.

Thanks in advance

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Answer 1

Jan 2013-9-11

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https://ww2.mathworks.cn/matlabcentral/answers/86854-how-to-convert-a-gray-scale-image-to-color-image-using-matlab#answer_96403

在 MATLAB Online 中打开

It depends on how the converted image should look like, so please explain any details. Examples:

Gray = rand(200, 200);
RGB1 = cat(3, Gray, Gray, Gray);  % information stored in intensity
RGB2 = Gray;
RGB2(end, end, 3) = 0;  % All information in red channel
GrayIndex = uint8(floor(Gray * 255));
Map       = jet(255);
RGB3      = ind2rgb(GrayIndex, Map);

And there are many many other possible solutions.

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Jule 2023-4-2

编辑：Jule 2023-4-2

tryin' to convert my unit8 image to green channel or blue channel, respectivel.

What should I change in:

RGB2 = Gray;

RGB2(end, end, 3) = 0; % All information in red channel

? Thnx

Image Analyst 2023-4-2

在 MATLAB Online 中打开

@Jule to split up into channels, you can use

[r, g, b] = imsplit(rgbImage);

r, g, and b will be gray scale versions of each color channel.

If you want to keep it as RGB you can blacken specific channels in place, like

% Make it look red by blackening the green and blue channels.
rgbCopy = rgbImage;
rgbCopy(:, :, 2) = 0; % Erase green channel.
rgbCopy(:, :, 3) = 0; % Erase blue channel.
% Make it look green by blackening the red and blue channels.
rgbCopy = rgbImage;
rgbCopy(:, :, 1) = 0; % Erase red channel.
rgbCopy(:, :, 3) = 0; % Erase blue channel.
% Make it look blue by blackening the red and green channels.
rgbCopy = rgbImage;
rgbCopy(:, :, 1) = 0; % Erase red channel.
rgbCopy(:, :, 2) = 0; % Erase green channel.

You can also use cat(3,...):

[r, g, b] = imsplit(rgbImage);
% Create an image of all zeros
blackImage = zeros(size(r, 1), size(r, 2), class(rgbImage));
% Make an RGB image look red by combining 
% the red channel with two black channels.
rgbCopy = cat(3, r, blackImage, blackImage);
% Make an RGB image look green by combining 
% the green channel with two black channels.
rgbCopy = cat(3, blackImage, g, blackImage);
% Make an RGB image look blue by combining 
% the blue channel with two black channels.
rgbCopy = cat(3, blackImage, blackImage, b);

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Answer 2

sidra 2013-9-11

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Nirmala , try the following , its a very simple and efficient code to convert grayscale images to RGB using a specified colormap.

http://www.mathworks.in/matlabcentral/fileexchange/13312-grayscale-to-rgb-converter

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Youssef Khmou 2013-9-12

编辑：Youssef Khmou 2013-9-12

So how they did retrieve old Black and White movies , made them Colored like they were recorded in RGB?

Image Analyst 2013-9-12

I believe I heard that most of that was done "by hand" - by artists - with some help from digital computers to continue colors onto the next frame. See https://en.wikipedia.org/wiki/Colorizing

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Answer 3

DGM 2022-5-2

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https://ww2.mathworks.cn/matlabcentral/answers/86854-how-to-convert-a-gray-scale-image-to-color-image-using-matlab#answer_955340

编辑：DGM 2022-5-2

在 MATLAB Online 中打开

cmancolorize.png

To answer the original intent of the question, there is no trivial way to return a grayscale image back to its original color. That information is gone. Your options are:

Go back to the source image before it was converted to grayscale
Manually colorize it by some means
Train an AI to guess what color a banana is

Only one of those options will get you back to the original image.

Otherwise, consider the conspicuously low-effort example of manual colorization:

A = imread('cameraman.tif');

B = imread('cmancolorize.png');

% i bet you didn't know cameraman was a smurf in a salmon shirt

Bycc = rgb2ycbcr(B);

Bycc(:,:,1) = 219*(im2double(A).^0.8) + 16;

C = ycbcr2rgb(Bycc);

imshow(C)

Honestly, I think it should be obvious that color information has been permanently lost. So I have to assume that the hundreds of people looking at this question every month are surely thinking of a less-than-obvious interpretation of the question.

With that in mind, there are a number of ways to add color information to a grayscale image. The following link covers a handful of ways, including simple colorization methods and basic application of colormaps.

https://www.mathworks.com/matlabcentral/answers/812105-grayscale-to-rgb-in-matlab

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Answer 4

Tallha Akram 2013-9-11

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[X,map] = imread('trees.tif');

gmap = rgb2gray(map);

figure, imshow(X,map), figure, imshow(X,gmap);

figure; imshow(X,gmap); colormap(map);

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Walter Roberson 2016-10-5

The appearance of vegetation is pretty sensitive to which IR band (and filtering) is being used, so you cannot assume that brightness is due entirely to temperature differences.

http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php

"The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4 to 0.7 µm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 µm). The more leaves a plant has, the more these wavelengths of light are affected, respectively."

So for that particular range of IR, "bright" can just mean that it has a lot of leaves reflecting ambient infrared preferably. See also http://www.nconemap.com/Portals/7/documents/Using_Color_Infrared_Imagery_20110810.pdf for more on how that property is used.

The situation is different if you measure in the far infrared; see https://en.wikipedia.org/wiki/Thermal_radiation

And notice, "The total amount of radiation of all frequencies increases steeply as the temperature rises; it grows as T^4, where T is the absolute temperature of the body."

Therefore if you had a way of measuring the total amount of radiation on all frequencies then you could take the fourth root to determine the proportional temperature. But you do not have a way to get that total radiation, and at the moment you do not know whether your sensors are linear in measuring that T^4.

So what do you need? Well, you can look for the frequency of peak radiation in the far infrared, under a black-body assumption. But to study peak frequency your equipment needs to be able to measure at multiple frequencies. If you have a greyscale image, chances are high that it is being measured over a band of frequencies in which all that can be registered is the total energy over that band, without being able to distinguish where the peak frequency was.

You need to find out a lot more about your available equipment.

Image Analyst 2016-10-31

Ask FLIR how to import the temperature matrix into MATLAB. I'm sure they must have code for doing that. Now you will have a matrix that has a spatial record of what temperature is where in your image, assuming you inputted the correct emissivity value. Ask FLIR because they might know what an accurate emissivity is for the type of plants you're looking at.

If you meant how to measure temperature directly, then look into thermocouples that interface with MATLAB. This will give you a "second opinion" on the temperature of the plants that you can check your camera against. Perhaps you can then adjust the emissivity of the camera until its values match the thermocouple's values.