A novel qutrit representation for RGB digital images
Mirna Rofail1, Rasha Montaser2, Ahmed Younes3,4
1Department of Mathematics and Computer Science, Faculty of Science, Alexandria University, Alexandria, 21526, Egypt. mirna.rofail@alexu.edu.eg.
Scientific Reports
|December 4, 2025
Summary
Ternary Quantum Image Processing (TQIP) uses qutrits for efficient image encoding. The new Ternary Novel Colored Quantum Representation (TNCQR) model requires fewer qutrits and simplifies quantum circuits for better performance.
Area of Science:
- Quantum Computing
- Image Processing
- Quantum Information Science
Background:
- Traditional Quantum Image Processing (QIP) uses binary quantum systems.
- Binary systems face limitations in information density and circuit complexity.
- There is a need for more efficient quantum image representation models.
Purpose of the Study:
- Introduce the Ternary Novel Colored Quantum Representation (TNCQR) model.
- Encode RGB digital images using a ternary quantum system.
- Enhance Quantum Image Processing (QIP) with qutrit-based systems.
Main Methods:
- Developed the Ternary Novel Colored Quantum Representation (TNCQR) model based on qutrits.
- Incorporated a single ancilla qutrit to reduce gate depth and quantum cost.
- Presented an optimization algorithm with general and conditional phases for circuit simplification.
Main Results:
- The TNCQR model requires fewer qutrits compared to equivalent binary models.
- Reduced circuit depth and improved time complexity through ancilla qutrit usage.
- Demonstrated an efficient, scalable, and resource-optimized quantum image representation.
Conclusions:
- Ternary Quantum Image Processing (TQIP) offers significant advantages over binary systems.
- The TNCQR model provides a more efficient and simplified approach to quantum image encoding.
- This research paves the way for advanced applications in quantum image processing.
Keywords:
Quantum image processingQuantum image representationQuantum ternary image circuitTernary logicMore Related Videos
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