I wrote my own scripts and programs for the whole workflow, from raw images processing, bad pixels removal and white balance, to alignment, to focus stacking, and multi-scale sharpening:
https://github.com/pulsar123/Macro-scripts
Very nice. Scripting around align_image_stack and enfuse, with additional processing
The reason I've asked for a test image sequence: I was recently asked by the Apertus folks to help them with a focus stack of a PCB, where align_image_stack was failing (and, as it turned out later, enfuse had suboptimal output on that image sequence). The main problem was the image sequence itself, which apparently was captured wide-open with an old manual lens; I've recommended them some new settings (along the lines of stopping down the aperture and using ISO 100, even if that meant a slightly long exposure), but re-shooting that particular PCB wasn't an option at the time (don't ask me why). So, I ended up rewriting align_image_stack and the focus stacking part of enfuse, from scratch, as Octave scripts, for that particular image sequence. Yes, in that case it was easier - for me - to reinvent the wheel, rather than fine-tuning the existing software.
When seeing your images, I thought my modified align_image_stack / enfuse versions might give slightly better output, so I was tempted to give it a try. Now that I see you are using an workflow based on align_image_stack and enfuse, you might be able to try them yourself (there are minimal modifications on the command line). Please find my scripts here:
http://files.apertus.org/align_image_stack/The first script is align_image_stack_finetune.m. It uses an initial brute force search, followed by coordinate descent (parameters: X and Y offsets, zoom aka focus breathing, optional rotation), first on low-resolution copies of the original images, then, increasing the resolution until 1/8 x 1/8 of the original (you can change that by editing the script). It aligns all the images in the sequence, to the middle image (as specified on the command line). It's significantly slower than the original align_image_stack, but it worked out of the box on the PCB test sequence (a few images available on that link, but not the entire sequence). It should handle images with tiny depth of field, where align_image_stack is unable to find its control points.
The second one is focus_stack.m, which outputs a weighted average of a pre-aligned image sequence. Weight is computed by looking at how much each image differs from a blurred copy of itself (computed as grayscale, for speed reasons). The output contains less halo artifacting, compared to enfuse, although I didn't use any deconvolution. I haven't tried it on other images.
Before:
PB5-enfuse.jpgAfter:
PB5-focus_stack.jpgIf you decide to try these scripts, please share the results. If this focus stacking algorithm can be useful to a wider audience, I'm happy to contribute it upstream (to be included in the official enfuse). With align_image_stack, it's a bit more complicated, as my approach is fundamentally different; besides, it would take significant work to convert it to another programming language (haven't checked the upstream sources yet).
