mlsanityData to 14 Oct 2026

A novel state connection strategy for quantum computing to represent and compress digital images

arXiv 2212.07079 ↗First posted 14 Dec 2022quant-ph cs.CV cs.CYcited by 1

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Abstract (arXiv)

Quantum image processing draws a lot of attention due to faster data computation and storage compared to classical data processing systems. Converting classical image data into the quantum domain and state label preparation complexity is still a challenging issue. The existing techniques normally connect the pixel values and the state position directly. Recently, the EFRQI (efficient flexible representation of the quantum image) approach uses an auxiliary qubit that connects the pixel-representing qubits to the state position qubits via Toffoli gates to reduce state connection. Due to the twice use of Toffoli gates for each pixel connection still it requires a significant number of bits to connect each pixel value. In this paper, we propose a new SCMFRQI (state connection modification FRQI) approach for further reducing the required bits by modifying the state connection using a reset gate rather than repeating the use of the same Toffoli gate connection as a reset gate. Moreover, unlike other existing methods, we compress images using block-level for further reduction of required qubits. The experimental results confirm that the proposed method outperforms the existing methods in terms of both image representation and compression points of view.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 29 references that are in the map. First posted on arXiv 14 Dec 2022.

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2 of 29 references.

References · 2

  1. 2015Faster than Classical Quantum Algorithm for dense Formulas of Exact Satisfiability and Occupation Problemscited by 2
  2. 2022Advance quantum image representation and compression using DCTEFRQI approachcited by 1

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