A Comprehensive Review on Classification of Quantum Image Representations

Document Type

Review

Publication Date

4-1-2026

Abstract

Quantum image processing (QIP) establishes a connection between quantum computation and image processing by utilizing diverse quantum image representations. This paper presents a comprehensive review of a number of quantum image representation techniques, categorizing them into four broad models, namely precision amplitude representation, threshold intensity representation, probabilistic state representation, and phase-based intensity representation. This paper further evaluated these QIR models based on several critical performance analyses, including the quantum circuit depth, the number of qubits employed, the time complexity associated with each model, entropy, and information losses. We have also highlighted state-of-the-art studies that have addressed QIR and its applications in various fields of image processing. This paper concludes by illuminating the strengths and limitations of each QIR technique which can lay the basis for future work to obtain better QIP algorithms. As a result, it paves the way for more efficient and powerful quantum computing applications in image processing and beyond.

Publication Title

Archives of Computational Methods in Engineering

ISSN

11343060

DOI

10.1007/s11831-025-10369-7

Volume

33

Issue

3

First Page

3123

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