13 papers
Circular Quasiconformal Deturbulence: Geometry-Based Restoration from Multiple Turbulent Frames
Chu Chen, Han Zhang, Lok Ming Lui
Imaging through inhomogeneous media often results in severe distortions, posing significant challenges to downstream image-processing tasks. The lack of clean paired images makes s…
Quasi-Conformal Convolution : A Learnable Convolution for Deep Learning on Simply Connected Open Surfaces
Han Zhang, Tsz Lok Ip, Lok Ming Lui
Deep learning on non-Euclidean domains is important for analyzing complex geometric data that lacks common coordinate systems and familiar Euclidean properties. A central challenge…
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis
Han Zhang, Qiguang Chen, Lok Ming Lui
Images degraded by geometric distortions pose a significant challenge to imaging and computer vision tasks such as object recognition. Deep learning-based imaging models usually fa…
Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Framework
Chenran Lin, Lok Ming Lui
This paper presents the Harmonic Beltrami Signature Network (HBSN), a novel deep learning architecture for computing the Harmonic Beltrami Signature (HBS) from binary-like images.…
Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimization
Zhehao Xu, Lok Ming Lui
Free-boundary diffeomorphism optimization, an important and widely occurring task in geometric modeling, computer graphics, and biological imaging, requires simultaneously determin…
Two-chart Beltrami Optimization for Distortion-Controlled Spherical Bijection with Application to Brain Surface Registration
Zhehao Xu, Lok Ming Lui
Many genus-0 surface mapping tasks such as landmark alignment, feature matching, and image-driven registration, can be reduced (via an initial spherical conformal map) to optimizin…