Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/ayax537/image-processing

This MATLAB GUI serves as a versatile tool for educational purposes in image processing, providing a hands-on approach to exploring various techniques and their effects on images. Users can experiment with different parameters and visualize the results in real-time.
https://github.com/ayax537/image-processing

image-processing matlab

Last synced: about 1 month ago
JSON representation

This MATLAB GUI serves as a versatile tool for educational purposes in image processing, providing a hands-on approach to exploring various techniques and their effects on images. Users can experiment with different parameters and visualize the results in real-time.

Awesome Lists containing this project

README 

        
# Image Processing Project

# Description

The Final_Project is an image processing application developed in MATLAB, designed to provide users with a comprehensive set of tools for manipulating and analyzing images. This project aims to facilitate learning and experimentation with various image processing techniques through an intuitive graphical user interface (GUI).



# Features

1. Image Loading and Display

File Selection: Users can easily load JPEG images from their local filesystem using a file selection dialog.

Dynamic Display: Loaded images are displayed in designated axes within the GUI, allowing for immediate visual feedback.

2. Image Resizing

Custom Dimensions: Users can input specific width and height values to resize images, making it convenient for preparing images for different applications.

3. Brightness Adjustment

Interactive Adjustment: Users can modify the brightness of the loaded images by specifying an offset value, enabling fine-tuning of brightness levels.

4. Gamma Correction

Non-linear Brightness Adjustment: Users can apply gamma correction to images, allowing for sophisticated control over the brightness and contrast of images based on user-defined gamma values.

5. Filtering Techniques

Mean Filtering: This feature enables users to apply mean filters to reduce noise and smooth images, which is essential for enhancing image quality.

Median Filtering: Users can apply median filters to effectively remove noise while preserving edges, making it ideal for applications requiring edge detection.

6. Histogram Analysis

Histogram Calculation: The application computes and displays the histogram of pixel values, providing insights into image brightness and contrast.

Histogram Equalization: Users can apply histogram equalization to enhance the contrast of images, making details more visible.

7. Histogram Matching

Contrast Enhancement: This feature allows users to match the histogram of one image to another, facilitating better contrast and brightness alignment between different images.

8. Color Manipulation

Grayscale Conversion: Users can convert images to grayscale, simplifying the image for further processing or analysis.

Channel Manipulation: The application allows users to manipulate individual color channels, enabling custom color effects and transformations.

9. Edge Detection

Basic Edge Detection: Users can apply edge detection algorithms to highlight edges in images, which is crucial for various computer vision applications.

10. Noise Addition

Gaussian Noise: Users can add Gaussian noise to images for testing purposes, allowing them to evaluate the robustness of different image processing techniques.

11. User-Friendly Interface

Intuitive Layout: The GUI is designed for ease of use, with clear labels and instructions for each feature.

Real-Time Feedback: Changes are immediately reflected in the GUI, enabling users to see the effects of their adjustments in real time.

# Conclusion

The Final_Project is an educational and practical tool for anyone interested in learning about image processing. With its diverse set of features, users can explore fundamental concepts and techniques, enhancing their understanding of how various image processing methods affect visual data. This project serves as an excellent resource for both beginners and advanced users in the field of image processing.