On the Uphill Battle of Image frequency Analysis
Nader Bazyari, Hedieh Sajedi
TL;DR
This paper explores the use of 3D Fast Fourier Transform on images to uncover hidden patterns, building upon a new clustering algorithm for non-homogeneous data.
Contribution
It formulates a specialized case of the Inverse Square Mean Shift Algorithm for non-homogeneous data and investigates Fourier analysis for pattern detection.
Findings
Identifies hidden patterns in images using Fourier analysis.
Extends clustering algorithm to handle non-homogeneous data.
Provides insights into frequency domain analysis of images.
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.
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