Abstract
Efficiently representing and compressing large-scale images in quantum circuits remains a challenge due to increasing circuit complexity. This paper proposes an innovative approach called NZ-NEQR (Non-Zero Novel Quantum Representation) to tackle this issue. Eliminating zero connections from the existing NEQR approach significantly reduces the complexity of state label preparation. The proposed NZ-NEQR approach achieves remarkable improvements
in both image representation and compression, leading to a substantial reduction in required bits per pixel. To further enhance compression, Block Truncation Coding (BTC) is adopted as a compression scheme, which effectively truncates images into two labels suitable for quantum compression and reconstruction. Notably, the proposed method requires fewer bits per pixel compared to existing NEQR approaches. Additionally, NZ-NEQR combined with BTC employs only 5 qubits for representing a 1024 × 1024 image, and compression using a 4 × 4 quantum BTC block represents a significant advancement. Computational results demonstrate the superior effectiveness of the proposed NZ-NEQR approach combined with
BTC for quantum image representation and compression, surpassing the performance of NEQR and JPEG approaches.
in both image representation and compression, leading to a substantial reduction in required bits per pixel. To further enhance compression, Block Truncation Coding (BTC) is adopted as a compression scheme, which effectively truncates images into two labels suitable for quantum compression and reconstruction. Notably, the proposed method requires fewer bits per pixel compared to existing NEQR approaches. Additionally, NZ-NEQR combined with BTC employs only 5 qubits for representing a 1024 × 1024 image, and compression using a 4 × 4 quantum BTC block represents a significant advancement. Computational results demonstrate the superior effectiveness of the proposed NZ-NEQR approach combined with
BTC for quantum image representation and compression, surpassing the performance of NEQR and JPEG approaches.
| Original language | English |
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| Title of host publication | Proceedings, 2023 International Conference on Digital Image Computing: Techniques and Applications |
| Subtitle of host publication | DICTA2023 |
| Place of Publication | United States |
| Publisher | IEEE Xplore |
| Pages | 304-311 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798350382204 |
| ISBN (Print) | 9798350382211 (Print on demand) |
| DOIs | |
| Publication status | Published - 30 Nov 2023 |
| Event | The International Conference on Digital Image Computing: Techniques and Applications: DICTA 2023 - Sails Port Macquarie, Port Macquarie, Australia Duration: 28 Nov 2023 → 01 Dec 2023 https://www.dictaconference.org/ https://www.dictaconference.org/?page_id=2623 (Conference program) |
Conference
| Conference | The International Conference on Digital Image Computing: Techniques and Applications |
|---|---|
| Country/Territory | Australia |
| City | Port Macquarie |
| Period | 28/11/23 → 01/12/23 |
| Other | Digital Image Computing: Techniques and Applications (DICTA) is the main Australian Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established in 1991 as the premier conference of the Australian Pattern Recognition Society (APRS). DICTA provides a forum for researchers, engineers, and practitioners to present their latest findings and innovations in these areas, as well as to exchange ideas and discuss emerging trends and challenges in the field. The conference covers a wide range of topics, including image and video processing, machine learning, pattern recognition, and computer graphics, among others. |
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