基于量子蒙霍夫变换的图像处理

Jincheng Zhang

Published Aug 28, 2026• 0 citations

Abstract

This paper explores the application of Quantum Монхоуф Transform (QMT) for image processing, specifically focusing on lossless compression and manipulation. Traditional image processing techniques often introduce information loss, leading to degradation in image quality. We propose utilizing the QMT, a quantum mechanical analogue of the Монхоуф Transform, to achieve lossless image processing. The core concept involves encoding image data into the basis vectors of the QMT and subsequently leveraging the QMT's inherent properties for image transformation. This approach draws upon both quantum information theory and the principles of the Монхоуф Transform, offering a novel pathway for efficient and lossless image handling. The theoretical framework and potential advantages of this method are presented, outlining a promising direction for future research in quantum image processing. The key mathematical framework is built upon the concept of quantum superposition and measurement, central to the QMT. The primary goal is to demonstrate a method for lossless image manipulation without the inherent distortions of conventional approaches.

DOI: 10.5281/zenodo.22138988

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