Image Processing Operations in C++

This project contains implementations of basic image processing operations using Dr. Cem’s simple C++ image library (image.h). Each file corresponds to an individual image operation we covered in class and is meant to help reinforce the concepts we practiced on paper — now in code.

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📂 Files Overview

Each .cpp file corresponds to a different image processing technique:

Filename	Description
nearestNeighbor.cpp	Nearest neighbor interpolation
bilinearInterpolation.cpp	Bilinear interpolation
brighten.cpp	Brightening the image
contrast.cpp	Adjusting contrast
gamma.cpp	Gamma correction
contrastStretching.cpp	Contrast stretching
inverse.cpp	Image inversion
histogramEqualization.cpp	Histogram equalization
convolution.cpp	Convolution with a blur kernel
image.h	Dr. Cem's simple image library (from Moodle)

Also included:

• lena.png: Original image
• lena_grayscale.png: Grayscale version for comparison (helps verify your results)

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How to Compile and Run

Each file is independent. To compile and run any of them, use the terminal commands below. Just replace the filename with the one you want.

🐧 On Linux:

Install the PNG development library:

• Ubuntu/Debian:

  sudo apt install libpng-dev

• Fedora:

  sudo dnf install libpng-devel

Then compile and run:

g++ -lpng yourfile.cpp -o yourprogram
./yourprogram

On Windows:

You’ll need to install a C++ compiler that supports PNG, such as MinGW or Visual Studio.
A video tutorial will be added soon to help with setup on Windows.

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✅ How It Works

Each .cpp file:

1. Loads lena.png or lena_grayscale.png.
2. Applies a specific image processing operation.
3. Saves the result to a new output file (like output_convolution.png, etc).

All implementations mirror the same math we did manually in class — now automated with C++.

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Tips

• The grayscale version is great for comparing visual effects after applying operations.
• The code is commented to help you understand what's going on step-by-step.
• Feel free to tweak the code and try different images (just update the filename in the code).

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Good luck with your exams!

I hope this helps, and feel free to clone or fork and experiment as much as you want!