A Hybrid Quantum Encoding Algorithm of Vector Quantization for Image Compression

TL;DR

This paper introduces a hybrid quantum-classical vector quantization encoding algorithm for image compression that reduces computational complexity compared to classical and pure quantum methods, enhancing efficiency.

Contribution

It presents a novel hybrid quantum VQ encoding algorithm that outperforms pure quantum algorithms in efficiency by reducing operations to less than sqrt(N).

Findings

Operates with fewer than sqrt(N) operations for most images.

More efficient than pure quantum VQ encoding algorithms.

Applicable to image compression tasks.

Abstract

Many classical encoding algorithms of Vector Quantization (VQ) of image compression that can obtain global optimal solution have computational complexity O(N). A pure quantum VQ encoding algorithm with probability of success near 100% has been proposed, that performs operations 45sqrt(N) times approximately. In this paper, a hybrid quantum VQ encoding algorithm between classical method and quantum algorithm is presented. The number of its operations is less than sqrt(N) for most images, and it is more efficient than the pure quantum algorithm. Key Words: Vector Quantization, Grover's Algorithm, Image Compression, Quantum Algorithm