# Tag Info

### From Uniform to 2D gaussian

The Gaussian distribution is separable. Apply your transformation to each coordinate separately and you will get a 2D Gaussian. If $G(x)$ is a 1D Gaussian, then $G(x) G(y)$ is a 2D Gaussian. Thus, ...
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### Histogram Equalization

Assuming that in your question $T(r)$ denotes a map $:\mathbb{R}\to[0,1]$ and assuming that it is continuous and strictly increasing, then it is obviously an isomorphism among $r\in[0,1]$ onto its ...
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### Histogram Counts of a 2d Matrix

Are you looking for a specific function to perform this task? Otherwise this could probably be done with a simple for loop. Determine your unique rows using the function bins = unique(A, 'rows'); ...
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### Histogram estimation (from sub-set of image pixels)

I think random sampling approach seems to be not effective, since the statistical population (pixel intensities) distribution in images is heavily localized. There might be more scientific approaches, ...
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### What Information Is Lost by Histogram Equalization?

Brightness. You can find more detailed information in here: Bi-Histogram Equalization with Brightness Preservation Using Contras Enhancement
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### What Information Is Lost by Histogram Equalization?

The expectation of information is called entropy. The loss of information can hence be understood as difference in entropy between source and processed image, assuming no random effect was added. ...
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If the distinct contents/ingredients really have different colors than you just have to take a picture, always in the same location/distance, and then count the amount of pixels for each color. You ...
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### Lightweight test for bimodal distributions?

If the test is just to test the hypothesis that there is noise vs. the hypothesis that there is noise plus some bimodal signal, then I would compare the mean absolute value of the signal, or some ...
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### Lightweight test for bimodal distributions?

An easy way, especially one that is used in the detection and SNR estimation of PSK signals in a noisy signal, is based on stochastic moments of the received amplitude: The kurtosis can be used as ...
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### How can I create a histogram showing the RMS amplitude for each frequency bin of an audio file

If what you want is to determine the amount of energy your signal has in particular frequency bands you can perform a FFT of your signal. For that you need to make sure that you have amplitude data ...
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### Image Contrast Enhancement Threshold Selection

What you are looking for called Otsu Method / Otsu Thresholding. It solves an optimization problem to set the optimal threshold between two modal distribution.
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### Histogram Counts of a 2d Matrix

The consolidator function by J. d'Errico (a solid contributor to MatlabCentral, with heavily optimized and versatile code) can be quite useful here. For your ...
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### purpose of histogram equalization

Contrast enhancement is usually the goal here, and making the histogram more uniform is the means to achieve it. Additionally, histogram equalization is useful for reducing the effects of varying ...
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### Help on choosing compatibility test for classification algoritm

Looking at both signals, there seems to be some semi-periodic component in the accepted signal that you can use, for example by doing a correlation based analysis: Your bottom signal looks like white ...
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### Inverse of filtering and inverse of equalization

Let's do a simple 1-D discrete combfilter. The impulse response is given $$h[n] = x[n] + g\cdot x[n-M]$$ I.e. a direct part and a reflection at time $M$ with a gain of $g$. The z-transform of that ...
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### Inverse of filtering and inverse of equalization

A comb filter with zeros cannot be inverted. At least not in a linear fashion without using som assumption about the signal. I don’t think that histogram equalization can generally be inverted either. ...
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### How can I create a histogram showing the RMS amplitude for each frequency bin of an audio file

There are two different ways to do this: Bandpass filter and then calculate RMS Do short term Fourier transform and Unless you have a really large number of bands, method number 1 is the better one. ...
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### The Math of Histogram Matching

The steps are as following: Calculate the CDF of each PDF: ${p}_{r} \left( r \right ) \rightarrow {P}_{r} \left( r \right ), \; {p}_{z} \left( z \right ) \rightarrow {P}_{z} \left( z \right )$. Map ...
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### 'Combed' Histograms

This might be hardware / software specific. You can reproduce this kind of artifact with a "simple window" that tries to map a narrow range of the original scale to a wider range. Each individual ...
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### Making images taken under daylight conditions appear as if they were taken at night using image processing elementary techniques

That really doesn't make sense: you'd be training a neural network to mimic a conversion algorith, which you already have. That's a waste of electricity ;) I doubt the resulting nets would generalize ...
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### How to plot histogram of difference of two images using MATLAB

Let us suppose that images are coded on uint8, hence integers in $[0,\ldots,255]$. For the difference image, values can range from $0-255$ or $255-0$, the maximum ...
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### How to plot histogram of difference of two images using MATLAB

In your second line, casting with uint8() will change a negative value to 0. Avoid casting or change to another type that supports negative values.
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### What Information Is Lost by Histogram Equalization?

There are different approaches to histogram equalization. Most typical approach essentially maps intensity levels $I_k$ into new ones $I_m$ based on a premise that new image would look better in ...
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### What Information Is Lost by Histogram Equalization?

The answer really depends on the histogram equalization you are using. If in the process there is either differentiation, quantization, re-binning or clipping, some information will be lost. The ...
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### What Is a Weighted Local Histogram?

A weighted local histogram would mean filtering the image $I(x,y)$ with a localised filter $H(x,y)$ (gaussian in this example). The resultant image is the 2D convolution $Y(x,y) = I(x,y)*H(x,y)$. The ...
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### Entropy of enhanced image more than the original image

According to me, the above relation should always hold true, According to the data processing theorem (and here), this is always true. how can an enhanced image contain more information than the ...
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### Calculating an HSV histogram

Since you want an histogram, I believe you want to plot it. In GNU Octave you may use hist3 and make three histograms (one for each pair: HxS, HxV and SxV). The code follows bellow: ...
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### Histogram Equalization Ignoring zero in Python

Actually, this is not a signal processing quesiton, and would have been better at stackoverflow. Anyway, you can use a look-up-table for this problem. The output value of a pixel does only depend on ...
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Accepted

### How to Generate a vector map for histogram equalization

Your code is halfway correct; it creates the cumulative distribution function (CDF), but the map isnt quite there yet. First you get the histogram using imhist(), but we want to convert this to ...
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