Image Dehazer

Welcome to Image Dehazer, a Python tool for removing haze from images. This repository provides a comprehensive solution for enhancing the clarity and quality of hazy images.

Features

• Removal of haze from images using a guided filter-based algorithm.
• Graphical user interface (GUI) for easy selection and processing of images.
• Sample input images provided for testing the tool.

File Structure

The repository is organized as follows:

• gf.py: Contains functions for guided filtering.

• haze_remover.py: Implements the haze removal algorithm using guided filtering.

• main.py: Provides a graphical user interface (GUI) for selecting and processing images.

• Sample Input Images: Provides the images for testing and demonstration.

• img/: Directory containing sample input images (src.jpg, dark.jpg, trans.jpg, gtrans.jpg) and the resulting dehazed image (dst.jpg).

  1. src.jpg: Original hazy image, serving as input for haze removal.
  2. dark.jpg: Dark channel prior of the original hazy image.
  3. trans.jpg: Estimated transmission map of the original hazy image.
  4. gtrans.jpg: Alternative transmission map estimation for comparison.
  5. dst.jpg: Resulting dehazed image after applying Image Dehazer algorithm.

• dehazed.jpg: Resulting dehazed image after processing using the tool.

• requirements.txt: To specify the dependencies required by the project.

Installation

Getting started with Image Dehazer is simple. Follow these steps to set up the tool on your machine:

1. Clone Repository: Clone this repository to your local machine:

    git clone https://github.com/Danish-Jamil-01/Image-Dehazer.git

2. Navigate to Directory: Move into the cloned repository directory:

    cd Image-Dehazer

3. Install Dependencies: Install the required dependencies using pip:

    pip install -r requirements.txt

Parameters by default

• radius=7
• omega=0.95
• t0=0.1
• r=20
• eps=0.001

Usage

After installing the dependencies, you can use the Image Remover Tool as follows:

1. Run Script: Execute the main.py script to launch the graphical user interface (GUI):

    python main.py

2. Select Image: Use the GUI to select an image for haze removal. Alternatively, you can manually enter the image path.

3. Process Image: Click the "Submit" button to initiate the haze removal process. The tool will display the dehazed image in the GUI.

4. Save Output: The dehazed image will be saved as dehazed.jpg in the repository directory.

Demo

Input:

Output:

Contributing

Contributions to this project are welcome. Feel free to open an issue or submit a pull request.

References

• Single Image Haze Removal using Dark Channel Prior
• Guided Image Filtering
• Single Image Dehazing via Conditional Generative Adversarial Network
• Single image dehazing based on learning of haze layers
• Dark channel prior in low frequency domain for time-efficient single image dehazing

License

This project is licensed under the MIT License.