shinestacker 1.0.2

ShineStacker

Shine Stacker

Focus Stacking Processing Framework and GUI

Focus stacking for microscopy, macro photography, and computational imaging

Key Features

• 🚀 Batch Processing: Align, balance, and stack hundreds of images
• 🧩 Modular Architecture: Mix-and-match processing modules
• 🖌️ Retouch Editing: Final interactive retouch of stacked image from individual frames
• 📊 Jupyter Integration: Image processing python notebooks

Interactive GUI

The GUI has two main working areas:

• Project: manage and run focus stacking workflows in a flexible and configurable way, with optional intermediate batch stacking.

• Retouch: select interactively details from individual frames and apply final filters to the blended image.

Resources

🌍 Website on WordPress • 📖 Main documentation • 📝 Changelog

Credits

The first version of the core focus stack algorithm was initially inspired by the Laplacian pyramids method implementation by Sami Jawhar that was used under permission of the author. The implementation in the latest releases was rewritten from the original code.

Resources

• Pyramid Methods in Image Processing, E. H. Adelson, C. H. Anderson, J. R. Bergen, P. J. Burt, J. M. Ogden, RCA Engineer, 29-6, Nov/Dec 1984 Pyramid methods in image processing
• A Multi-focus Image Fusion Method Based on Laplacian Pyramid, Wencheng Wang, Faliang Chang, Journal of Computers 6 (12), 2559, December 2011

License

- **Code**: The software is provided as is under the [GNU Lesser General Public License v3.0](https://www.gnu.org/licenses/lgpl-3.0.en.html). See [LICENSE](https://github.com/lucalista/shinestacker/blob/main/LICENSE) for details.

• Logo: The Shine Stacker logo was designed by Alessandro Lista. Copyright © Alessandro Lista. All rights reserved. The logo is not covered by the LGPL-3.0 license of this project.

Attribution request

📸 If you publish images created with Shine Stacker, please consider adding a note such as:

Created with Shine Stacker – https://github.com/lucalista/shinestacker

This is not mandatory, but highly appreciated.