Welcome to BigFeta’s documentation!

BigFeta is a scalable linear least squares image stitching and alignment solver that can align millions of images via point correspondences. The solver runs on systems from individual workstations to distributed clusters.

This solver was developed to provide the image alignment steps for [Mahalingam19]. The starting point for this package was the MATLAB-based package described in [KDS18]. This solver is described in [Kapner19].

Compared to that repository, this repository has a number of changes and additions:

	[KDS18]	this repo
language	MATLAB	Python, C for external
external solver	PaStiX	multiple, via PETSc
external solver installation	independent of repo	included in Singularity container
transforms	translation rigid approximation affine polynomial to 3rd degree	translation rigid via rotation transform affine polynomial to arbitrary degree thin plate spline
automated tests	N/A	TravisCI

The User Guide

Use cases and detailed explanations of input parameters.

• User Guide
  • Use cases
  • Important Dependencies
  • Detailed Argument Descriptions
  • Distributed Usage

API

This contains the complete documentation of the api

• BigFeta
  • BigFeta schema
  • BigFeta
  • utils
  • transforms
  • jsongz
• BigFeta distributed
  • Class Hierarchy
  • File Hierarchy
  • Full API

Indices and tables

• Index
• Module Index
• Search Page

References

[Kapner19]

Daniel Kapner… Tbd. TBD, 2019. URL: TBD, arXiv:TBD.

[KDS18]

(1, 2) Khaled Khairy, Gennady Denisov, and Stephan Saalfeld. Joint deformable registration of large EM image volumes: A matrix solver approach. CoRR, 2018. URL: http://arxiv.org/abs/1804.10019, arXiv:1804.10019.

[Mahalingam19]

Gayathri Mahalingam… Tbd. TBD, 2019. URL: TBD, arXiv:TBD.

Acknowledgement of Government Sponsorship

Supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior / Interior Business Center (DoI/IBC) contract number D16PC00004. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/IBC, or the U.S. Government.