rescale histogram
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hello all !
i need to rescale the x-axis(gray levels) of a histogram from 0-1 to 0-255 ! can anyone help me ?! ,i need it coz i've to calculate pdf then.. thank you
2 个评论
Geoff
2012-4-30
Post the code you are having issues with. If you are using the 'hist' command, you can solve a lot of issues by using 'histc' to generate an array, and then draw it into a bar graph.
mohammed ABDEEN
2012-5-1
回答(3 个)
Image Analyst
2012-4-30
0 个投票
If your image has value in the range 0-255 then how did you get bins in the 0-1 range? You must be looking at an image that has been transformed, perhaps by im2double. Maybe you should just take the histogram of the original image, or else multiply the image you took the histogram of by 255 and cast to uint8 and take the histogram of that instead.
9 个评论
mohammed ABDEEN
2012-5-1
mohammed ABDEEN
2012-5-1
Image Analyst
2012-5-2
I don't see why you need to scale the intensity ranges of the two images so that they match. And, even if you did, why stop at just matching the min and max? Why not match the whole histogram, like in my histogram matching app (http://www.mathworks.com/matlabcentral/fileexchange/28972-custom-shaped-histogram) or like http://www.eyemaginary.com/Portfolio/ColorHistogramWarp.html
mohammed ABDEEN
2012-5-2
Image Analyst
2012-5-2
Yes, to calculate entropy (http://en.wikipedia.org/wiki/Entropy_%28information_theory%29) you find the histogram and then divide by the number of pixels in the image, then do sum(p.*log(p)). So the *counts* are scaled to within 0 and 1. Most likely no bins will hit 1 unless you have only one signal gray level in your image. But I don't see why the scaling of the gray levels is required. In your terminology, you scale p, but not i (where i is the gray level). I just don't see how the entropy formula has gray level in it - I see only the scaled counts (i.e., "p") in it. Am I missing something?
mohammed ABDEEN
2012-5-2
Geoff
2012-5-2
To transform the normalised grey level to an integer, you multiply by 256 (or 255, if you insist) and round the result. I thought the entire concept of entropy is a tendency to approach infinity... =P
Image Analyst
2012-5-2
You still haven't convinced me, and I doubt you will. The probability values in the probability density function do not depend on the bin value. The probability values will of course depend on the width of the bins, and the location of the bins with respect to the true distribution, but simply scaling the bins (what you call i or gray level) will not change the PDF, and thus not change p in sum(p*log p), and not change entropy. Try it and see. If you don't see, ask me and I'll make a demo for you to prove it.
mohammed ABDEEN
2012-5-3
Geoff
2012-5-2
Still not sure I understand your motive completely...
But it seems like you have this situation:
data = rand(100,1);
bins = (1:4)/4 - 1/8;
hist(data, bins);
And you want this:
hist(data*256, bins*256);
set(gca, 'XLim', [0 256]);
set(gca, 'XTick', linspace(0,256,5));
10 个评论
mohammed ABDEEN
2012-5-2
mohammed ABDEEN
2012-5-2
Geoff
2012-5-2
What do you mean "it doesn't work"? If you think this answer is close but can't make it work with your modifications, then post your modifications so we can have a better guess at what you want.
Image Analyst
2012-5-2
It could be because he took your code and calculated the entropy, and he got the same entropy no matter which histogram he used. That's what I've been trying to tell him, but he hasn't realized it yet - he's still expects that the entropy of the image when the intensity values are in the range 0-1 will somehow be different and less accurate than when they are scaled from 0-255. You and I know that's not true but he's not convinced. The PDF = pixelCount / numel(pixelCount) and this doesn't depend on the bin values (the "x", or the value at the center of the bin, or gray level values, or his "i", or however you want to describe it). Maybe you can take a shot at explaining it to him.
mohammed ABDEEN
2012-5-3
Image Analyst
2012-5-3
So either divide the bin values by 255 so the bins now go from 0-1 instead of 0-255 (but don't divide the pixel counts), or else divide the image by 255 and then use hist() or imhist(). Either way should get you the same thing.
mohammed ABDEEN
2012-5-3
mohammed ABDEEN
2012-5-3
mohammed ABDEEN
2012-5-3
mohammed ABDEEN
2012-5-3
Junaid
2012-5-2
0 个投票
I guess if you normalize your histogram, you will your desired output .. May be ?
As after normalizing your histogram, the sum of all values will be 1. That is actually you want (all values in Histogram will be in between 0-1).
Easiest way to normalize is to divide histogram by sum of histogram.
3 个评论
Image Analyst
2012-5-3
No, he wanted the intensity values to go from 0-1, not the count values.
Junaid
2012-5-3
Oh... thanks for letting me know.
mohammed ABDEEN
2012-5-3
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