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Histogram

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The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
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Related Experiment Video

Updated: Jun 9, 2026

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Published on: February 29, 2012

A novel 3-D color histogram equalization method with uniform 1-D gray scale histogram.

Ji-Hee Han¹, Sejung Yang, Byung-Uk Lee

¹Electronics Engineering Department, Ewha W. University, Seoul, Korea. jiheehan87227@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|August 31, 2010

Summary

Existing color histogram equalization methods fail to produce uniform grayscale histograms, degrading image contrast. This study introduces a novel 3-D color histogram equalization technique for improved grayscale uniformity and contrast in digital images.

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Area of Science:

Digital Image Processing
Computer Vision

Background:

Most color histogram equalization techniques result in non-uniform grayscale histograms.
Grayscale conversion after color equalization leads to inferior contrast compared to 1-D grayscale equalization.

Purpose of the Study:

To propose a novel 3-D color histogram equalization method.
To achieve uniform grayscale histogram distribution.
To analyze and compare existing color histogram equalization algorithms.

Main Methods:

Development of a new cumulative probability density function in 3-D color space.
Implementation of a 3-D color histogram equalization algorithm.
Testing with natural and synthetic images.

Main Results:

The proposed 3-D method achieves uniform grayscale histogram distribution.
Demonstrated superior contrast in converted grayscale images compared to existing methods.
Provided theoretical analysis of non-ideal performance in current algorithms.

Conclusions:

The novel 3-D color histogram equalization method effectively enhances image contrast and grayscale uniformity.
This approach offers a significant improvement over traditional color equalization techniques.
Further analysis confirms the theoretical underpinnings of the proposed method.