On the Uphill Battle of Image frequency Analysis

arXiv cs.CV / 4/10/2026

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Key Points

  • The paper follows up on the newly proposed Inverse Square Mean Shift Algorithm, extending it via a special case for non-homogeneous data.
  • It investigates a three-dimensional Fast Fourier Transform (FFT) approach for images to detect hidden or latent patterns.
  • The work is positioned as part of ongoing research into clustering and signal-processing techniques for extracting structure from complex image data.
  • The focus is methodological and exploratory, aiming to improve how frequency-domain analysis can reveal patterns that may be difficult to find in the spatial domain.

Abstract

This work is a follow up on the newly proposed clustering algorithm called The Inverse Square Mean Shift Algorithm. In this paper a special case of algorithm for dealing with non-homogenous data is formulated and the three dimensional Fast Fourier Transform of images is investigated with the aim of finding hidden patterns.