Quantum Block-Matching Algorithm using Dissimilarity Measure

TL;DR

This paper introduces a quantum block-matching algorithm that employs a dissimilarity measure based on quantum Fourier transform or Swap test, demonstrating its potential on quantum devices for applications like image processing.

Contribution

It proposes a novel quantum dissimilarity measure for block-matching, utilizing quantum Fourier transform and Swap test, tested on real quantum hardware.

Findings

Successful implementation on IBM and IonQ quantum devices.

Potential for near-term quantum applications in image processing.

Effective in small-scale simulations with ideal and noisy conditions.

Abstract

Finding groups of similar image blocks within an ample search area is often necessary in different applications, such as video compression, image clustering, vector quantization, and nonlocal noise reduction. A block-matching algorithm that uses a dissimilarity measure can be applied in such scenarios. In this work, a measure that utilizes the quantum Fourier transform or the Swap test based on the Euclidean distance is proposed. Experiments on small cases with ideal and noisy simulations are implemented. In the case of the Swap test, the IBM and IonQ quantum devices have been used, demonstrating potential for future near-term applications.