Aduku Stacker vs Shine Stacker

Aduku Stacker combines photographs taken at different focus distances into a sharp image, for macro, product, landscape and microscopy photography. The free app offers five merge methods: Wavelet, Pyramid, Weighted, Hybrid and Depthmap. Its default workflow processes images at 16-bit and uses 32-bit floating-point merge calculations, with memory-bounded batching for deep stacks. Automatic alignment uses feature matching and subpixel refinement; options include focus-breathing correction, homography, mesh warp and manual alignment seeding. It imports JPEG, PNG, TIFF, BMP, HEIC and DNG, and exports JPEG, PNG, TIFF, linear DNG and depth maps. Proprietary RAW files may require Adobe DNG Converter on macOS. Retouching lets users paint from aligned source frames, erase strokes and undo or redo, but there is no clone tool. Processing is local and does not require an internet connection. It runs on macOS 13 or later and 64-bit Windows 10/11; 8 GB RAM is sufficient for most stacks, with 16 GB recommended for deep 16-bit RAW stacks.

Shine Stacker combines images captured at different focus distances to produce images with extended depth of field. It is intended for microscopy, macro photography, and computational imaging. The software offers Laplacian pyramid and depth map stacking methods, with automatic alignment, color or luminosity balancing, noisy pixel masking, vignetting correction, and final filters. For retouching, users can select details from individual frames to address dust, ghosts, and artifacts. Batch workflows can divide many frames into smaller groups before merging them into one focused image. Python batch processing and Jupyter notebook scripting are supported. Shine Stacker supports RAW files and lists TIFF, JPEG, and multilayer TIFF as output formats. It is open source under the LGPL-3.0 license and free to download. The listed platforms are Windows, macOS, Linux, and API. The maker offers a GitHub download and Python installation through PyPI with pip.