Spherical harmonics entropy for optimal 3D modeling

TL;DR

This paper introduces a spherical harmonics entropy method for optimal 3D image reconstruction, demonstrating improved accuracy and efficiency in processing spherical shapes across various scientific fields.

Contribution

It proposes a novel spherical harmonics Shannon-type entropy approach for 3D image reconstruction, enhancing existing methods with a new entropy-based evaluation metric.

Findings

The method improves reconstruction accuracy for spherical models.

It demonstrates efficiency in processing spherical 3D images.

The approach is validated through simulation studies.

Abstract

3D image processing constitutes nowadays a challenging topic in many scientific fields such as medicine, computational physics and informatics. Therefore, development of suitable tools that guaranty a best treatment is a necessity. Spherical shapes are a big class of 3D images whom processing necessitates adoptable tools. This encourages researchers to develop spherical wavelets and spherical harmonics as special mathematical bases able for 3D spherical shapes. The present work lies in the whole topic of 3D image processing with the special spherical harmonics bases. A spherical harmonics based approach is proposed for the reconstruction of images provided with spherical harmonics Shannon-type entropy to evaluate the order/disorder of the reconstructed image. Efficiency and accuracy of the approach is demonstrated by a simulation study on several spherical models.