Quantum median filter for Total Variation image denoising
Simone De Santis, Damiana Lazzaro, Riccardo Mengoni, Serena Morigi

TL;DR
This paper introduces a quantum computing approach for image denoising using a quantum version of the Total Variation model, demonstrating competitive performance despite current quantum device limitations.
Contribution
It develops a novel Quantum TV method for image denoising, bridging quantum computing and image processing in an emerging research area.
Findings
Quantum TV achieves competitive denoising results.
The method demonstrates potential despite quantum hardware limitations.
The approach advances quantum image processing techniques.
Abstract
In this new computing paradigm, named quantum computing, researchers from all over the world are taking their first steps in designing quantum circuits for image processing, through a difficult process of knowledge transfer. This effort is named Quantum Image Processing, an emerging research field pushed by powerful parallel computing capabilities of quantum computers. This work goes in this direction and proposes the challenging development of a powerful method of image denoising, such as the Total Variation (TV) model, in a quantum environment. The proposed Quantum TV is described and its sub-components are analysed. Despite the natural limitations of the current capabilities of quantum devices, the experimental results show a competitive denoising performance compared to the classical variational TV counterpart.
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