Parallel Histogram Equalization GrayScale Images

Histogram equalization is a powerful technique used to enhance the contrast of images by adjusting the intensity distribution. In grayscale images, each pixel is represented by a single value denoting its intensity, typically ranging from 0 to 255. This value corresponds to the brightness of the pixel, with 0 representing black and 255 representing white.

Purpose:

This project aims to implement histogram equalization for grayscale images using parallel processing techniques, specifically leveraging the Message Passing Interface (MPI) for distributed computing. By utilizing MPI along with C++, we can distribute the workload across multiple processing units, such as CPU cores or compute nodes, to accelerate the histogram equalization process.

Tools Used:

• C++: The project is developed using the C++ programming language, providing high performance and flexibility for implementing complex algorithms.

• MPI (Message Passing Interface): MPI is utilized for distributed computing, enabling communication and coordination among multiple computing nodes or processes for parallel execution.

Credits:

• Mohamed Samy
• Yomna Mohamed
• Nadine Haitham