PowerSpectR: An R Package for Radial Power Spectrum Estimation

TL;DR

PowerSpectR is an R package that estimates and visualizes radial Fourier power spectra from imaging data, emphasizing robustness against localized features and artifacts.

Contribution

It introduces a median-based radial power spectrum estimation workflow combining edge mitigation, Fourier analysis, and radial binning, with an open-source implementation.

Findings

Provides a robust method for spectral analysis of images.

Reduces bias from bright sources and artifacts.

Available at https://github.com/RafaelSdeSouza/PowerSpectR.

Abstract

I present here PowerSpectR, an R package for computing and visualizing median-based radial Fourier power spectra from imaging data. Power spectra provide a representation of spatial structure by decomposing contributions across spatial scales, and the resulting slopes can serve as compact, low-dimensional summaries of morphological complexity across images. PowerSpectR provides a workflow for estimating these slopes, combining edge-effect mitigation through Hann windowing, Fourier-domain analysis, and radial binning with azimuthal median statistics. The use of median aggregation helps to reduce sensitivity to bright compact sources, masking artifacts, and other localized features that can bias standard estimators. PowerSpectR is released under the MIT license at \href{https://github.com/RafaelSdeSouza/PowerSpectR}{this repository}.