# Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning

arXiv: https://arxiv.org/abs/2204.11133 · HTML: https://mlsanity.com/paper/2204.11133/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 34 references that are in the map.
- First posted on arXiv 23 Apr 2022.

## Builds on (most cited first, 1 of 1)

- [Supervised learning with quantum enhanced feature spaces](https://mlsanity.com/paper/1804.11326/) (2018)

## Built on by (most cited first, 5 of 5)

- [Better than classical? The subtle art of benchmarking quantum machine learning models](https://mlsanity.com/paper/2403.07059/) (2024)
- [QuaCK-TSF: Quantum-Classical Kernelized Time Series Forecasting](https://mlsanity.com/paper/2408.12007/) (2024)
- [Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms](https://mlsanity.com/paper/2510.07317/) (2025)
- [Gradient Flows for L2 Support Vector Machine Training](https://mlsanity.com/paper/2208.04365/) (2022)
- [Kernel k-Medoids as General Vector Quantization](https://mlsanity.com/paper/2506.04786/) (2025)

## Abstract (arXiv)

Given is a set of images, where all images show views of the same area at different points in time and from different viewpoints. The task is the alignment of all images such that relevant information, e.g., poses, changes, and terrain, can be extracted from the fused image. In this work, we focus on quantum methods for keypoint extraction and feature matching, due to the demanding computational complexity of these sub-tasks. To this end, k-medoids clustering, kernel density clustering, nearest neighbor search, and kernel methods are investigated and it is explained how these methods can be re-formulated for quantum annealers and gate-based quantum computers. Experimental results obtained on digital quantum emulation hardware, quantum annealers, and quantum gate computers show that classical systems still deliver superior results. However, the proposed methods are ready for the current and upcoming generations of quantum computing devices which have the potential to outperform classical systems in the near future.