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# histeq

Enhance contrast using histogram equalization

## Syntax

``J = histeq(I,hgram)``
``J = histeq(I,n)``
``````[J,T] = histeq(I)``````
``newmap = histeq(X,map)``
``newmap = histeq(X,map,hgram)``
``````[newmap,T] = histeq(X,___)``````

## Description

example

````J = histeq(I,hgram)` transforms the grayscale image `I` so that the histogram of the output grayscale image `J` with `length(hgram)` bins approximately matches the target histogram `hgram`.You optionally can perform histogram equalization of grayscale images using a GPU (requires Parallel Computing Toolbox™). For more information, see Image Processing on a GPU.```
````J = histeq(I,n)` transforms the grayscale image `I`, returning in `J` an grayscale image with `n` discrete gray levels. A roughly equal number of pixels is mapped to each of the `n` levels in `J`, so that the histogram of `J` is approximately flat. The histogram of `J` is flatter when `n` is much smaller than the number of discrete levels in `I`. ```
``````[J,T] = histeq(I)``` returns the grayscale transformation `T` that maps gray levels in the image `I` to gray levels in `J`.```
````newmap = histeq(X,map)` transforms the values in the colormap so that the histogram of the gray component of the indexed image `X` is approximately flat. It returns the transformed colormap in `newmap`.This syntax is not supported on a GPU.```
````newmap = histeq(X,map,hgram)` transforms the colormap associated with the indexed image `X` so that the histogram of the gray component of the indexed image (`X`,`newmap`) approximately matches the target histogram `hgram`. The `histeq` function returns the transformed colormap in `newmap`. `length(hgram)` must be the same as `size(map,1)`.This syntax is not supported on a GPU.```
``````[newmap,T] = histeq(X,___)``` returns the grayscale transformation `T` that maps the gray component of `map` to the gray component of `newmap`.This syntax is not supported on a GPU.```

## Examples

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Read an image into the workspace.

`I = imread('tire.tif');`

Enhance the contrast of an intensity image using histogram equalization.

`J = histeq(I);`

Display the original image and the adjusted image.

```imshowpair(I,J,'montage') axis off```

Display a histogram of the original image.

```figure imhist(I,64)```

Display a histogram of the processed image.

```figure imhist(J,64)```

`load mristack`

Perform histogram equalization.

`enhanced = histeq(mristack);`

Display the first slice of data for the original image and the contrast-enhanced image.

```figure subplot(1,2,1) imshow(mristack(:,:,1)) title('Slice of Original Image') subplot(1,2,2) imshow(enhanced(:,:,1)) title('Slice of Enhanced Image')```

This example performs the same histogram equalization on the GPU.

```I = gpuArray(imread('tire.tif')); J = histeq(I); figure imshow(I) figure imshow(J)```

## Input Arguments

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Input grayscale image, specified as a numeric array of any dimension.

To perform histogram equalization using a GPU, specify `I` as a `gpuArray` that contains a numeric array of any dimension.

Data Types: `single` | `double` | `int16` | `uint8` | `uint16`

Target histogram, specified as a numeric vector. `hgram` has equally spaced bins with intensity values in the appropriate range:

• [0, 1] for images of class `double` or `single`

• [0, 255] for images of class `uint8`

• [0, 65535] for images of class `uint16`

• [-32768, 32767] for images of class `int16`

`histeq` automatically scales `hgram` so that `sum(hgram)=numel(I)`. The histogram of `J` will better match `hgram` when `length(hgram)` is much smaller than the number of discrete levels in `I`.

If you perform histogram equalization using a GPU, then you optionally can specify `hgram` as a `gpuArray` that contains a numeric vector.

Data Types: `single` | `double`

Number of discrete gray levels, specified as a scalar.

Data Types: `single` | `double`

Indexed image, specified as a numeric array of any dimension. The values in `X` are an index into the colormap `map`.

Data Types: `single` | `double` | `uint8` | `uint16`

Colormap, specified as an c-by-3 array. Each row specifies an RGB color value.

Data Types: `double`

## Output Arguments

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Output grayscale image, returned as a numeric array of the same size and class as the input image `I`.

If histogram equalization is performed using a GPU, then `J` is returned as a `gpuArray` containing a numeric array.

Grayscale transformation, returned as a numeric vector. The transformation `T` maps gray levels in the image `I` to gray levels in `J`.

If histogram equalization is performed using a GPU, then `T` is returned as a `gpuArray` containing a numeric vector.

Data Types: `double`

Transformed colormap, specified as an n-by-3 array. Each row specifies an RGB color value.

Data Types: `double`

## Algorithms

When you supply a desired histogram `hgram`, `histeq` chooses the grayscale transformation T to minimize

`$|{c}_{1}\left(T\left(k\right)\right)-{c}_{0}\left(k\right)|,$`

where c0 is the cumulative histogram of `A`, c1 is the cumulative sum of `hgram` for all intensities k. This minimization is subject to the constraints that T must be monotonic and c1(T(a)) cannot overshoot c0(a) by more than half the distance between the histogram counts at a. `histeq` uses the transformation b = T(a) to map the gray levels in `X` (or the colormap) to their new values.

If you do not specify `hgram`, then `histeq` creates a flat `hgram`,

`hgram = ones(1,n)*prod(size(A))/n;`

and then applies the previous algorithm.