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IBEABFHR

Image Brightness Enhancement Automatically Based on Fast Haze Removal

Install / Use

/learn @rzwm/IBEABFHR
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Automatically enhance image brightness based on fast haze removal[1]. Support 24-bit RGB image and 8-bit gray image.

Development Environment

  • Microsoft Visual Studio Community 2017
  • Windows 10
  • OpenCV 3.3.0
  • x64

Getting Started

  1. Open IBEABFHR.sln with Microsoft Visual Studio 2017;
  2. Config OpenCV according this Install OpenCV with Visual Studio;
  3. Press Ctrl+B to build program;
  4. Press F5 to run program;

Run Time

resolution | type | time ---|---|--- 1024x768 | gray | 8.77ms 1024x768 | color | 16.24ms 1920x1080 | gray | 22.61ms 1920x1080 | color | 40.60ms 4160x2340 | gray | 104.57ms 4160x2340 | color | 186.14ms

The times above are the average time for call brighten100 times. If you just call brighten one times, the run time will be larger, because the first time doing image invert operation consumes extra time for unknown reason.

Adjust Parameters

There has two variable parameters :

  1. radius in step 3, as the box filter radius. This parameter should not too small, otherwise result image will has halo artifact.
  2. p in step 5, which controlls the result image's brightness. Bigger is it, brighter is the result image.

Effect Display

2.jpg 2_brighten.jpg 2_gray.jpg 2_gray_brighten.jpg

Reference

[1] 刘倩, 陈茂银, 周东华. 基于单幅图像的快速去雾算法[C]//25th Chinese Control and Decision Conference, 2013: 3780-3785.

Related Skills

View on GitHub
GitHub Stars36
CategoryDevelopment
Updated1mo ago
Forks13

Languages

C++

Security Score

95/100

Audited on Mar 5, 2026

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