Bijective Density-Equalizing Quasiconformal Map for Multiply-Connected Open Surfaces
Not on the map. Why?
Abstract (arXiv)
This paper proposes a novel method for computing bijective density-equalizing quasiconformal (DEQ) flattening maps for multiply-connected open surfaces. In conventional density-equalizing maps, shape deformations are solely driven by prescribed constraints on the density distribution, defined as the population per unit area, while the bijectivity and local geometric distortions of the mappings are uncontrolled. Also, prior methods have primarily focused on simply-connected open surfaces but not surfaces with more complicated topologies. Our proposed method overcomes these issues by formulating the density diffusion process as a quasiconformal flow, which allows us to effectively control the local geometric distortion and guarantee the bijectivity of the mapping by solving an energy minimization problem involving the Beltrami coefficient of the mapping. To achieve an optimal parameterization of multiply-connected surfaces, we develop an iterative scheme that optimizes both the shape of the target planar circular domain and the density-equalizing quasiconformal map onto it. In addition, landmark constraints can be incorporated into our proposed method for consistent feature alignment. The method can also be naturally applied to simply-connected open surfaces. By changing the prescribed population, a large variety of surface flattening maps with different desired properties can be achieved. The method is tested on both synthetic and real examples, demonstrating its efficacy in various applications in computer graphics and medical imaging.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Aug 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 3; 2026: 3.
6 papers.
- 2025Learning-based density-equalizing mapcited by 2
- 2025Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimizationcited by 1
- 2025Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problemscited by 0
- 2026Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Frameworkcited by 0
- 2026Resolution-free neural surrogates for geometric parameterization and mapping with spatially varying fieldscited by 0
- 2026Learning Task-Aware Sampling with Shared Saliency through Density-Equalizing Mappingscited by 0
- 2026Learning Task-Aware Sampling with Shared Saliency through Density-Equalizing Mappings11 Jun 2026
- 2026Resolution-free neural surrogates for geometric parameterization and mapping with spatially varying fields27 May 2026
- 2026Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Framework3 Mar 2026
- 2025Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimization12 Nov 2025
- 2025Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problems31 Oct 2025
- 2025Learning-based density-equalizing map10 Jun 2025