Histogram equalization on 16 bit images. (As of 9th February 2019) While OpenCV can perform histogram equalization, it only works on 8 bit images.

This project shows how to perform histogram equalization directly on 16 bit images (without downsampling to 8 bit).

This project will read 16 bit grayscale image(HistogramEqualization\Image\16bit_grayscale.TIF), perform histogram equalization and save the output in "HistogramEqualization\Output\16bit_grayscale.TIF".

Please find the histogram equalization method in Histogram\Histogram.cpp. It is based on similar OpenCV method equalizeHist().

This project uses CMAKE. This project requires you to have precompiled OpenCV library.

1. Clone this project

2. Edit CMakeLists.txt at the root folder of this project to set the correct OpenCV path.

   # Make sure to configure this block
   ###############################################################################
   set(OpenCV_DIR "D:/Project/DurrNDT/opencv")
   # we want to copy OpenCV bin files to build dir
   set(OpenCV_BIN_DIR "D:/Project/DurrNDT/opencv/x64/vc15/bin") 
   ###############################################################################
   

3. If you are not using OpenCV 4.0.1, make appropriate changes in the same CMakeLists.txt

   find_package(OpenCV 4.0.1 REQUIRED)
   

4. Configure and generate using cmake/cmake-gui

   

5. Find generated .sln and compile with Visual Studio.

6. Execute HistogramEqualization.exe and check the output image in "Output\16bit_grayscale.TIF"

Histogram-Test is the testing project. It uses googletest framework.

Speed of the method can be improve (potentially) by

• parallel processing
• uses OpenCL
• uses OpenVX

I uses platform specific function in the main function. This can be improved by using C++17(among others).

Histogram equalization method depends on OpenCV.

• OpenCV
• googletest
• cmake

• Syaiful Nizam Yahya

• Nick D'Ademo