contrast gain of an image

3 次查看（过去 30 天）

Silpa K 2019-10-22

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/486755-contrast-gain-of-an-image

评论： Silpa K 2019-11-5

I have an image that from an hazy image model,a haze free image.I need to find the contrast gain of this image.How can I find that,please help me.

回答（1 个）

Image Analyst 2019-10-22

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/486755-contrast-gain-of-an-image#answer_397639

Perhaps look at the ratio of the ranges, or the standard deviations, unless you have a specific formula someone recommends.

15 个评论
显示 13更早的评论隐藏 13更早的评论

Image Analyst 2019-11-1

在 MATLAB Online 中打开

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures if you have the Image Processing Toolbox.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 14;
rng default
% Image and parameters
% grayImage = imread('cameraman.tif');
grayImage = imread('pout.tif');
[rows, columns, numberOfColorChannels] = size(grayImage)
startTime = tic;
if numberOfColorChannels > 1
	% It's not gray scale, it's color, so convert to gray scale.
	grayImage = rgb2gray(grayImage);
end
doubleImage = im2double(grayImage);
tot = sum(double(doubleImage(:)));
% Compute some factors.
A = ((1 ./ (rows*columns)) * tot);
stdDevOriginal = std2(doubleImage);
t1 = doubleImage ./ A;
t2 = stdDevOriginal * t1;
t = 1 - t2;
fprintf('Starting de-hazing process...\n');
% Define your function, make sure it is element-wise
Hazy = @(I, A, t) (I - A * (1 - t)) ./ t; 
% Apply the function to the double image.
J1 = Hazy(doubleImage, A, t);
stdDevProcessed = std(J1(:));
contrastGain = stdDevProcessed / stdDevOriginal;
elapsedTime = toc(startTime);
fprintf('Done with de-hazing process.\nIt took %.2f seconds.', elapsedTime);
subplot(2, 2, 1)
imshow(doubleImage)
caption = sprintf('Original image.  StdDev = %.3f', stdDevOriginal);
title(caption, 'FontSize', fontSize);
axis('on', 'image');
impixelinfo;
subplot(2, 2, 2)
imshow(J1)
caption = sprintf('Processed Image.  StDev = %.3f\n with contrast gain %.2f', ...
	stdDevProcessed, contrastGain);
title(caption, 'FontSize', fontSize);
axis('on', 'image');
impixelinfo;
subplot(2, 2, 3)
imshow(t)
title('The "t" image', 'FontSize', fontSize);
axis('on', 'image');
impixelinfo;
%------------------------------------------------------------------------------
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
% 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')
message = sprintf('Done!\nThe elapsed time was %.3f seconds.', elapsedTime);
fprintf('%s\n', message);
uiwait(helpdlg(message));

How gigantic is your image? For my demo image, I see

rows =

291

columns =

240

numberOfColorChannels =

Starting de-hazing process...

Done with de-hazing process.

It took 0.01 seconds.Done!

The elapsed time was 0.011 seconds.

Note that it took only a hundredth of a second, not 5 minutes. Also note that the haze removal is not that good. You might want to investigate your algorithm further (I did not do that - I just took the formula you gave).