  Background noise in many fields such as medical imaging poses significant
challenges for accurate diagnosis, prompting the development of denoising
algorithms. Traditional methodologies, however, often struggle to address the
complexities of noisy environments in high dimensional imaging systems. This
paper introduces a novel quantum-inspired approach for image denoising, drawing
upon principles of quantum and condensed matter physics. Our approach views
medical images as amorphous structures akin to those found in condensed matter
physics and we propose an algorithm that incorporates the concept of mode
resolved localization directly into the denoising process. Notably, our
approach eliminates the need for hyperparameter tuning. The proposed method is
a standalone algorithm with minimal manual intervention, demonstrating its
potential to use quantum-based techniques in classical signal denoising.
Through numerical validation, we showcase the effectiveness of our approach in
addressing noise-related challenges in imaging and especially medical imaging,
underscoring its relevance for possible quantum computing applications.
