https://github.com/rahulpatel2002/imageprocessing-edgedetection

MATLAB implementation of edge detection using Laplacian operators, unsharp masking, and highboost filtering. This lab explores various filtering techniques to enhance image features.
https://github.com/rahulpatel2002/imageprocessing-edgedetection

convolution-filter edge-detection highboost-filter image-processing laplacian-filter matlab unsharp-masking

Last synced: about 1 year ago
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MATLAB implementation of edge detection using Laplacian operators, unsharp masking, and highboost filtering. This lab explores various filtering techniques to enhance image features.

• Host: GitHub
• URL: https://github.com/rahulpatel2002/imageprocessing-edgedetection
• Owner: RAHULPATEL2002
• Created: 2025-01-28T16:20:59.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-02-03T18:25:43.000Z (over 1 year ago)
• Last Synced: 2025-03-17T05:18:16.800Z (over 1 year ago)
• Topics: convolution-filter, edge-detection, highboost-filter, image-processing, laplacian-filter, matlab, unsharp-masking
• Language: MATLAB
• Homepage:
• Size: 7.81 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# **Finding Edges in Images**

## **AIM**

The objective of this MATLAB script is to find the edges in a grayscale image by applying the following edge detection operators:

1. Laplacian Operator

2. Unsharp Masking

3. Highboost Filtering

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## **Features**

This MATLAB script performs the following tasks:

- Converts an image to grayscale (if not already grayscale).

- Applies various Laplacian filters with different center coefficients.

- Enhances image sharpness using Unsharp Masking.

- Performs Highboost Filtering to improve image details.

- Displays and compares results visually.

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## **How to Use**

1. Clone or download this repository to your local system.

2. Ensure MATLAB (R2020b or later) and the Image Processing Toolbox are installed.

3. Run the script `lab09_edges.m` in MATLAB.

4. The script will display the results of different edge detection methods including Laplacian, Unsharp Masking, and Highboost Filtering.

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## **Prerequisites**

- MATLAB R2020b or later.

- Image Processing Toolbox.

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## **Instructions**

1. Save the file as `lab09_edges.m`.

2. Open MATLAB and navigate to the directory containing the script.

3. Run the script in MATLAB by typing `lab09_edges` in the command window.

4. The script will:

   - Read and convert the input image to grayscale.

   - Apply Laplacian filters with different coefficients.

   - Perform Unsharp Masking with different kernel sizes.

   - Apply Highboost Filtering with different boost factors.

   - Display the processed images in separate figure windows.

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## **Example Results**

### **Laplacian Edge Detection**

![Screenshot 2025-02-02 211018](https://github.com/user-attachments/assets/318da6fd-c870-4e47-bc52-2f36f69da0cc)

### **Unsharp Masking**

![Screenshot 2025-02-02 211028](https://github.com/user-attachments/assets/ad83a36c-eb30-4d2b-bd71-cfd12069e4f8)

### **Highboost Filtering**

![Screenshot 2025-02-02 211040](https://github.com/user-attachments/assets/ca3ee9ae-3fb2-463e-83f1-1da8e8c4d87d)

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## **Author**

**Rahul Patel**  

*Electronics and Communication Engineering Student*  

*Date: Febrary 02, 2025*

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