astrot3k-common

Create a mini-application named 'AstroProcessor' using the Python package 'astrot3k-common'. This application will serve as a command-line tool designed to assist astronomers and astrophotographers in processing their images captured from telescopes or other astronomical imaging devices. The primary goal of AstroProcessor is to streamline common tasks such as noise reduction, star alignment, and basic image enhancement, making it easier for users to focus on more complex aspects of their work without being bogged down by repetitive tasks.

### Features:
- **Noise Reduction**: Implement a feature that allows users to reduce noise in their images. This could include options for different types of noise reduction techniques.
- **Star Alignment**: Provide functionality for aligning stars across multiple images taken at different times or angles, ensuring consistency in long-exposure photography.
- **Basic Image Enhancement**: Offer tools for basic enhancements like adjusting brightness, contrast, and color balance.
- **Batch Processing**: Enable users to process multiple images at once, saving time and effort.
- **Output Options**: Allow users to choose the format and quality of the output files.

### Utilization of 'astrot3k-common':
- Use 'astrot3k-common' to handle shared utilities such as logging, file handling, and configuration management, which are essential for maintaining a clean and efficient codebase.
- Leverage any specific utilities within 'astrot3k-common' that support astronomical image processing tasks, such as pre-processing routines or data validation functions.

### Steps to Build AstroProcessor:
1. **Setup Environment**: Install necessary dependencies including 'astrot3k-common', and set up a virtual environment for Python.
2. **Design CLI Interface**: Create a user-friendly command-line interface that allows users to input commands for various operations.
3. **Implement Core Functions**: Develop the core functionalities of noise reduction, star alignment, and image enhancement, utilizing the utilities provided by 'astrot3k-common' where applicable.
4. **Add Batch Processing Capabilities**: Integrate batch processing so users can process multiple images simultaneously.
5. **Test Thoroughly**: Conduct rigorous testing to ensure all features work as expected and that there are no bugs or performance issues.
6. **Documentation**: Write comprehensive documentation explaining how to use AstroProcessor, including examples and best practices.
7. **Deployment**: Package AstroProcessor into a distributable form, such as a standalone executable or a pip-installable package, making it easy for others to use.

By following these steps and utilizing the 'astrot3k-common' package effectively, you'll create a powerful yet accessible tool for astronomers and astrophotographers looking to enhance their workflow.