🌙 Lunar Crater Image Enhancement

An advanced web application for enhancing images of lunar Permanently Shadowed Regions (PSR) using state-of-the-art image processing algorithms.

🚀 Features

• Multiple Enhancement Methods

  • Multi-Scale Retinex
  • Adaptive Gamma Correction
  • Guided Image Filter
  • Laplacian Pyramid Enhancement
  • Frequency Domain Enhancement
  • Traditional Methods (Bilateral Filter, CLAHE, Unsharp Masking)

• Advanced Analysis

  • Comprehensive metrics (PSNR, SSIM, Entropy, etc.)
  • Real-time parameter adjustments
  • Side-by-side comparison
  • Detailed performance metrics

• User-Friendly Interface

  • Intuitive parameter controls
  • Dark/Light theme support
  • Real-time preview
  • Interactive results comparison
  • Downloadable enhanced images

🛠️ Technologies Used

• Backend

  • Python 3.x
  • Flask
  • OpenCV (cv2)
  • NumPy
  • SciPy
  • scikit-image

• Frontend

  • HTML5
  • CSS3
  • JavaScript (Vanilla)
  • Modern UI with responsive design

📋 Prerequisites

• Python 3.x
• pip package manager
• Web browser with modern JavaScript support

🔧 Installation

1. Clone the repository:

   git clone https://github.com/maitrisavaliya/lunar-crater-enhancer.git
   cd lunar-crater-image-enhancer

2. Install required packages using pip:

   pip install -r requirements.txt

🚀 Running the Application

Web Interface

Start the web server:

python app.py

Then open your browser and navigate to:

http://localhost:5000

Command Line Interface (CLI)

Process images directly from the command line:

# Basic enhancement with default settings
python enhance.py --input image.jpg --output enhanced.jpg

# Multi-Scale Retinex enhancement
python enhance.py --input image.jpg --output enhanced.jpg --method retinex --sigma 15,80,250 --gain 1.2

# Adaptive Gamma correction
python enhance.py --input image.jpg --output enhanced.jpg --method gamma --base 0.8 --sensitivity 0.3

# Process multiple images
python enhance.py --input ./input_folder --output ./output_folder --method retinex

# Get help and see all options
python enhance.py --help

💡 Usage

1. Upload a lunar crater image through the web interface
2. Select desired enhancement methods:
   • Enable/disable specific algorithms
   • Adjust parameters for each method
3. Click "Process Image" to apply enhancements
4. Compare results and metrics in the interactive viewer
5. Download enhanced images as needed

📊 Enhancement Methods

Novel Methods

1. Multi-Scale Retinex

   • Illumination normalization based on human visual perception
   • Excellent for uneven lighting conditions
   • Customizable scales for detail preservation

2. Adaptive Gamma Correction

   • Spatially-varying gamma correction
   • Automatic adjustment to local brightness
   • Preserves detail in shadows and highlights

3. Guided Image Filter

   • Edge-preserving smoothing
   • Superior to traditional bilateral filtering
   • Linear time complexity

4. Laplacian Pyramid Enhancement

   • Multi-resolution detail enhancement
   • Controllable detail boosting
   • Preserves global structure

5. Frequency Domain Enhancement

   • FFT-based selective frequency boosting
   • Separate control of low and high frequencies
   • Advanced detail recovery

Traditional Methods

• Bilateral Filter
• CLAHE (Contrast Limited Adaptive Histogram Equalization)
• Unsharp Masking

License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Authors

• Your Name - Initial work - YourGitHub

🙏 Acknowledgments

• NASA for lunar imagery resources
• OpenCV community for image processing tools
• Scientific papers and research in image enhancement