Adjusting CData to match CLim for grayscale Image

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John 2016-4-21

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评论： John 2016-4-22

I have a grayscale image in a figure displayed through imshow. I adjust the axes CLim limits [a b] to improve it's contrast to desired levels. How can I adjust the image matrix (CData) to match the image displayed by my CLim limits? I've tried imadjust function i.e. Image2=imadjust(Image1,[a b],[]) , but the resultant Image2 contrast doesn't look like the one displayed by CLim limits [a b].

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Answer 1

Walter Roberson 2016-4-21

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在 MATLAB Online 中打开

t = double(max(min(Image1, b),a));
adjusted_image = (t - a) / (b - a);

now adjusted_image is in the range 0 (corresponding to a) to 1 (corresponding to b). Remember to caxis([0 1])

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John 2016-4-21

Exactly what I was looking for. I had a brain freeze :)

Thanks

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Answer 2

Image Analyst 2016-4-21

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What are you trying to do? If you want to stretch contrast, you can pass in the values you want for black and white into imshow(). Or else call caxis(). I don't understand why you would ask what you asked.

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Image Analyst 2016-4-22

在 MATLAB Online 中打开

Yeah it works but it's somewhat inefficient because it has to compute two intermediate images. Anyway, there's a function for doing that normalization - it's called mat2gray().

But John, I think you might have bee a little too quick to discard my answer. caxis just does a look up table modification so it's really fast and uses no extra memory. I think you just didn't know what I was suggesting so I give you an example:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format compact;
fontSize = 20;
format short g;
% Read in low contrast image.
imshow('pout.tif');
colormap(gray(256));
colorbar;
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off') 
promptMessage = sprintf('Click continue to adjust caxis');
titleBarCaption = 'Continue?';
buttonText = questdlg(promptMessage, titleBarCaption, 'Continue', 'Quit', 'Continue');
if strcmpi(buttonText, 'Quit')
  return;
end
for k = 1 : 5 : 200
  caxis([k, 255]);
  pause(0.1);
end
promptMessage = sprintf('Click continue to adjust caxis');
titleBarCaption = 'Continue?';
buttonText = questdlg(promptMessage, titleBarCaption, 'Continue', 'Quit', 'Continue');
if strcmpi(buttonText, 'Quit')
  return;
end
colormap(gray(256));
for k = 254 : -5 : 65
  caxis([0, k]);
  pause(0.1);
end
promptMessage = sprintf('Click continue to adjust caxis');
titleBarCaption = 'Continue?';
buttonText = questdlg(promptMessage, titleBarCaption, 'Continue', 'Quit', 'Continue');
if strcmpi(buttonText, 'Quit')
  return;
end
colormap(gray(256));
for k = 1 : 5 : 127
  caxis([k, 255-k]);
  pause(0.2);
end

Walter Roberson 2016-4-22

The intermediate images probably would not be too large.

John 2016-4-22

Thanks Robert. I had the GUI ready, just needed that part of adjusting the matrix. I've employed the mat2gray. I agree the caxis is more efficient, but I'm working with very small images (about 128x128pixel, 8bit) so in the end, the memory isn't an issue for now. I'll implement your suggestion if need be in the future.

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Adjusting CData to match CLim for grayscale Image

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Adjusting CData to match CLim for grayscale Image

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