histeq

Enhance contrast using histogram equalization

Syntax

J = histeq(I,hgram)

J = histeq(I,n)

J = histeq(I)

newmap = histeq(X,map)

newmap = histeq(X,map,hgram)

[___,T] = histeq(___)

Description

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.

J = histeq(I,n) transforms the grayscale image I so that the histogram of the output grayscale image J with n bins is approximately flat. The histogram of J is flatter when n is much smaller than the number of discrete levels in I.

J = histeq(I) transforms the grayscale image I so that the histogram of the output grayscale image J has 64 bins and is approximately flat.

newmap = histeq(X,map) transforms the values in the color map so that the histogram of the gray component of the indexed image X is approximately flat. The transformed color map is newmap.

newmap = histeq(X,map,hgram) transforms the color map 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 color map in newmap. length(hgram) must be the same as size(map,1).

[___,T] = histeq(___) also returns the transformation T that maps the gray component of the input grayscale image or color map to the gray component of the output grayscale image or color map.

Examples

Enhance Contrast Using Histogram Equalization

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)

Enhance Contrast of Volumetric Image Using Histogram Equalization

Load a 3-D dataset.

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')

Input Arguments

I — Input grayscale image

numeric array

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

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

hgram — Target histogram

numeric vector

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 better matches hgram when length(hgram) is much smaller than the number of discrete levels in I.

Data Types: single | double

n — Number of discrete gray levels

64 (default) | positive integer

Number of discrete gray levels, specified as a positive integer.

Data Types: single | double

X — Indexed image

numeric array

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

Data Types: single | double | uint8 | uint16

map — Color map

c-by-3 array

Color map, specified as a c-by-3 numeric matrix with values in the range [0, 1]. Each row is a three-element RGB triplet that specifies the red, green, and blue components of a single color of the color map.

Data Types: double

Output Arguments

J — Transformed grayscale image

numeric array

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

T — Grayscale transformation

numeric vector

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

Data Types: double

newmap — Transformed color map

n-by-3 numeric matrix

Transformed color map, specified as an n-by-3 numeric matrix with values in the range [0, 1]. Each row is a three-element RGB triplet that specifies the red, green, and blue components of a single color of the color map.

Data Types: double

Algorithms

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

$$\left|c_1(T(k))-c_0(k)\right|,$$

c₀ is the cumulative histogram of the input image I, and c₁ is the cumulative sum of hgram for all intensities k. This minimization is subject to these constraints:

• T must be monotonic

• 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 color map) 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.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• histeq supports the generation of C code (requires MATLAB^® Coder™). Note that if you choose the generic MATLAB Host Computer target platform, histeq generates code that uses a precompiled, platform-specific shared library. Use of a shared library preserves performance optimizations but limits the target platforms for which code can be generated. For more information, see Code Generation Using a Shared Library.

• When generating code, histeq does not support indexed images.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Image Processing on a GPU.