Butterfly Image Enhancement Using Digital Image Processing Techniques

This project focuses on enhancing butterfly images using Digital Image Processing techniques implemented from scratch with Python.

The project uses a real-world butterfly image dataset from Kaggle to improve image quality, reduce noise, enhance contrast, and highlight important image details.

**Key Features:**

- Image loading, visualization, and dataset analysis.

- Histogram Equalization and Contrast Stretching.

- Gaussian and Median Filtering for image smoothing and noise reduction.

- Laplacian Sharpening for edge enhancement.

- Frequency-domain processing using Fast Fourier Transform (FFT).

- Ideal Low-Pass and High-Pass Filtering.

- Visual comparison between original and processed images.

**Technologies Used:** Python, OpenCV, NumPy, Matplotlib, Kaggle.

The project demonstrates practical image preprocessing and enhancement techniques that can support future computer vision and image classification applications.