Which techniques can be applied instead of histogram binning?
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Hi I read a paper using latent dirichlet allocation (LDA), which author has created the intensity intervals for images to create the words ( intensity intervals), and the number pixels that fall into each interval (bin) is counted.However, this leads to poor performance in detecting low-contrast pixel intensities. My question is which technique can be used instead of histogram binning, how we can address this issue? I really do not know how we can tackle with this?
Your help is appreciated :)
Many thanks
5 Comments
Jan
on 1 Mar 2016
Please define "poor performance" with any details, because we cannot guess them. The term "faint" sounds to imply, that the results have a "poor performance".
Sara Salimi
on 1 Mar 2016
Edited: Sara Salimi
on 1 Mar 2016
Does "performance" concern the computing time or are the results "poor", because the pixels with low intensitied cannot be distinguished efficiently? You did not mention, what you want to achieve. All you mention is, that a certain method is "poor". But how can this be used to suggest a "better" method?
Image Analyst
on 1 Mar 2016
The low contrast pixels are there (not missing from the image), so what do you mean by "detecting low-contrast pixel intensities"? Contrast as computed over what region or window size? Why is a histogram needed? Why not just take the Laplacian of the image, with conv2(), and find values close to zero?
Sara Salimi
on 2 Mar 2016
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