Polyharmonic Daubechies type wavelets in Image Processing and Astronomy, II
Ognyan Kounchev, Damyan Kalaglarsky, Milcho Tsvetkov
TL;DR
This paper explores polyharmonic Daubechies-type wavelets for image processing, especially in astronomy, demonstrating advantages over standard wavelets and potential for improved image compression.
Contribution
Introduces polyharmonic subdivision wavelets of Daubechies type for image processing, showing their effectiveness in astronomical images and potential for better compression.
Findings
Polyharmonic Daubechies wavelets outperform standard multivariate wavelets.
Significant improvement in astronomical image processing.
Potential for enhanced image compression techniques.
Abstract
We consider the application of the polyharmonic subdivision wavelets (of Daubechies type) to Image Processing, in particular to Astronomical Images. The results show an essential advantage over some standard multivariate wavelets and a potential for better compression.
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.
Taxonomy
TopicsImage and Signal Denoising Methods · Advanced Image Fusion Techniques · Medical Image Segmentation Techniques