Underwater Image Enhancement towards NeRF-based 3D Reconstruction

Introduction

This project focuses on enhancing underwater images and utilizing these enhanced images for NeRF-based 3D reconstruction. Underwater imaging presents challenges such as haze, color distortion, low contrast, and loss of visibility. By improving the quality of underwater images, we aim to achieve more accurate 3D reconstructions using NeRF (Neural Radiance Fields) technology.

Objectives

1. Perform image enhancement on underwater images to address challenges such as haze, color distortion, and low contrast.
2. Utilize the enhanced images for 3D reconstruction using NeRF-based techniques.
3. Propose an efficient method for improving underwater image quality and visibility.
4. Validate the effectiveness of the algorithm through experiments and comparisons with existing techniques.

Problem Statement

The challenge is to develop a learning-based architecture for enhancing underwater images and leveraging these enhanced images for NeRF-based 3D reconstruction. This involves addressing issues such as haze, color distortion, and low visibility in underwater photographs.

Application in Societal Context

Enhancement of underwater images and 3D reconstruction have significant societal applications:

• Marine Conservation and Research: Improved visualization of underwater environments aids in marine conservation efforts and scientific research.
• Coral Reef Monitoring: Clearer images contribute to better monitoring and understanding of coral reef ecosystems.
• Underwater Surveillance for Protected Areas: Enhanced images can be used for surveillance in protected underwater areas.
• Naval Special Operations: Supports reconnaissance missions, underwater infiltration, hydrographic surveying, mine countermeasures, and counter-terrorism operations.
• Scientific Exploration: Enhancing underwater images benefits scientific exploration by providing clearer data for analysis.

Repository Structure

• Literature Survey/: Contains all the research paper related Underwater image enhancement and NeRF-based 3D reconstruction.
• main.ipynb/: Includes code for underwater images and datasets for testing and validation.
• report/: Documentation related to the project, including reports, presentations, and technical guides.
• final/: Stores the results of image enhancement and 3D reconstruction experiments.
• LICENSE: License information for the project.

Getting Started

To get started with this project, follow these steps:

1. Clone the repository to your local machine.
2. Navigate to the code/ directory and follow the instructions in the README file to run the image enhancement and 3D reconstruction algorithms.
3. Refer to the documentation in the docs/ directory for more detailed information about the project.

Contributing

Contributions to this project are welcome. If you have ideas for improvements or want to report issues, please open an issue or submit a pull request on GitHub.

License

This project is licensed under the MIT License, which allows for modification, distribution, and commercial use with proper attribution.