Quantization Opportunities for Polyharmonic Subdivision Wavelets Applied to Astronomical Images

TL;DR

This paper explores polyharmonic subdivision wavelets for astronomical images, analyzing coefficient distributions to inform better quantization methods, with experiments on Lena and astronomical images.

Contribution

It introduces a new family of multivariate wavelets and investigates their coefficient distributions to improve quantization in image processing.

Findings

Wavelet coefficient distributions differ between Lena and astronomical images.

Results suggest potential for tailored quantization algorithms based on distribution analysis.

Experimental data supports the applicability of polyharmonic subdivision wavelets in astronomical imaging.

Abstract

We continue the study of a new family of multivariate wavelets which are obtained by "polyharmonic subdivision". We provide the results of experiments considering the distribution of the wavelet coefficients for the Lena image and for astronomical images. The main purpose of this investigation is to find a clue for proper quantization algorithms.