Multivariate Quasi-tight Framelets with High Balancing Orders Derived from Any Compactly Supported Refinable Vector Functions
Bin Han, Ran Lu

TL;DR
This paper introduces a method to construct multivariate quasi-tight framelets with high vanishing moments and balancing orders from any compactly supported refinable vector functions, enhancing multiscale analysis tools.
Contribution
It develops a new approach using the oblique extension principle to derive quasi-tight framelets with optimal properties from arbitrary refinable vector functions.
Findings
Constructed multivariate quasi-tight framelets with maximal vanishing moments.
Achieved high balancing order in associated fast framelet transforms.
Provided theoretical foundations for multivariate quasi-tight framelets.
Abstract
Generalizing wavelets by adding desired redundancy and flexibility,framelets are of interest and importance in many applications such as image processing and numerical algorithms. Several key properties of framelets are high vanishing moments for sparse multiscale representation, fast framelet transforms for numerical efficiency, and redundancy for robustness. However, it is a challenging problem to study and construct multivariate nonseparable framelets, mainly due to their intrinsic connections to factorization and syzygy modules of multivariate polynomial matrices. In this paper, we circumvent the above difficulties through the approach of quasi-tight framelets, which behave almost identically to tight framelets. Employing the popular oblique extension principle (OEP), from an arbitrary compactly supported -refinable vector function with multiplicity greater than one, we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
