Signal and Image Processing (SIP)

Welcome to the Signal and Image Processing (SIP) repository, where we delve into the core concepts and applications of signal and image processing using practical, hands-on Jupyter notebooks.

Table of Contents

• Introduction
• Repository Structure
• Getting Started
• Notebooks Overview
• Contributing

Introduction

Signal and image processing is a vast field of study that encompasses techniques used to process, analyze, and interpret signals and images. This repository contains a series of Jupyter notebooks, each covering different fundamental topics and methods within this domain, from the basics of signals to the complexities of image processing algorithms.

Repository Structure

The repository is structured with all the Jupyter notebooks located within the src directory. Each notebook is named to reflect the topic it covers. For instance:

• 1_Basics_of_Signal_and_Image_Processing.ipynb
• 2_Signals_and_Operations_on_Signals.ipynb
• 3_DFT_and_IDFT_with_Twiddle_Factor_Matrix.ipynb
• ...and so on.

Getting Started

To use the notebooks in this repository:

1. Clone the repository to your local machine using: git clone https://github.com/dev02chandan/Signal-and-Image-Processing.git
2. Ensure you have Jupyter installed or use Google Colab to open the notebooks.
3. Start running the notebooks!

Notebooks Overview

Here's what you can expect to learn from the notebooks available:

• 1_Basics_of_Signal_and_Image_Processing: An introduction to the fundamental concepts in signal and image processing.
• 2_Signals_and_Operations_on_Signals: Exploring various operations that can be performed on signals.
• 3_DFT_and_IDFT_with_Twiddle_Factor_Matrix: Understanding the Discrete Fourier Transform and its inverse.
• 4_Spatial_and_Gray_Level_Resolution: Diving into spatial resolution and gray level resolution in images.
• 5_Image_Processing: Comprehensive coverage of standard image processing techniques.
• 6_Histogram_Processing_and_Equalization: Learning about histogram processing and image equalization.
• 7_Ideal_and_Butterworth_Filter: Filters in signal processing and their applications.
• 8_Edge_Detection_using_Sobels_Mask: Edge detection techniques in image processing.
• 9_Erosion_and_Dilation: Morphological operations in image processing.
• 10_Morphological_Operations_Opening_and_Closing: More on morphological operations and their uses.
• 11_Video_Processing: Techniques and methods for processing video data.

Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

Don't forget to give the project a star 🌟! Thanks again!