# Image comparison and scaling via nonlinear elasticity

arXiv: https://arxiv.org/abs/2303.10103 · HTML: https://mlsanity.com/paper/2303.10103/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 30 references that are in the map.
- First posted on arXiv 17 Mar 2023.

## Builds on (most cited first, 3 of 3)

- [Shape Aware Matching of Implicit Surfaces based on Thin Shell Energies](https://mlsanity.com/paper/1509.06559/) (2015)
- [A Hyperelastic Two-Scale Optimization Model for Shape Matching](https://mlsanity.com/paper/1507.07760/) (2015)
- [Symmetry and scaling limits for matching of implicit surfaces based on thin shell energies](https://mlsanity.com/paper/2009.01724/) (2020)

## Built on by (most cited first, 1 of 1)

- [A nonlinear elasticity model in computer vision](https://mlsanity.com/paper/2408.17237/) (2024)

## Abstract (arXiv)

A nonlinear elasticity model for comparing images is formulated and analyzed, in which optimal transformations between images are sought as minimizers of an integral functional. The existence of minimizers in a suitable class of homeomorphisms between image domains is established under natural hypotheses. We investigate whether for linearly related images the minimization algorithm delivers the linear transformation as the unique minimizer.