Image Processing Project

Overview

This project implements various image processing techniques using Python libraries such as NumPy, OpenCV, and Matplotlib. The key operations covered in this project include spatial operations, Fourier transforms, morphological operations, and image restoration.

Table of Contents

• Features
• Technologies Used
• Installation
• Usage
• Examples

Features

• Spatial Operations: Basic image manipulations such as resizing, cropping, and filtering.
• Fourier Transform: Frequency domain analysis using Fast Fourier Transform (FFT).
• Morphological Operations: Techniques such as erosion, dilation, opening, and closing.
• Image Restoration: Methods to restore images affected by blurring and noise.

Technologies Used

• Python
• NumPy
• OpenCV
• Matplotlib

Installation

To get started with this project, you need to have Python installed on your machine. You can install the required libraries using pip

Usage

You can read project instructions for each sub-project from pdf files and run .ipynb files

Examples

Here are some examples of the operations implemented in this project:

1. Spatial Filtering:

   • Apply a Gaussian blur to an image.

2. Fourier Transform:

   • Analyze the frequency components of an image.

3. Morphological Operations:

   • Perform erosion and dilation on binary images.

4. Image Restoration:

   • Restore a blurred image using Wiener filtering.