Multisegmentation through wavelets: Comparing the efficacy of Daubechies vs Coiflets

TL;DR

This study compares Daubechies and Coiflet wavelets for image segmentation, finding Coiflet wavelets outperform Daubechies in a fast statistical algorithm due to their mathematical properties.

Contribution

It provides a comparative analysis of wavelet families in image segmentation, highlighting the superior performance of Coiflet wavelets within a specific algorithm.

Findings

Coiflet wavelets outperform Daubechies in segmentation tasks

Coiflet wavelets satisfy mini-max conditions better

Daubechies wavelets better capture polynomial trends

Abstract

In this paper, we carry out a comparative study of the efficacy of wavelets belonging to Daubechies and Coiflet family in achieving image segmentation through a fast statistical algorithm.The fact that wavelets belonging to Daubechies family optimally capture the polynomial trends and those of Coiflet family satisfy mini-max condition, makes this comparison interesting. In the context of the present algorithm, it is found that the performance of Coiflet wavelets is better, as compared to Daubechies wavelet.