A novel qutrit representation for RGB digital images

Abstract

Abstract Ternary Quantum Image Processing (TQIP) leverages the power of qutrits to enhance Quantum Image Processing (QIP) by enabling higher information density, reducing error rates, and simplifying circuit complexity compared to traditional binary quantum systems. Inspired by the ENEQR binary model, this paper introduces the Ternary Novel Colored Quantum Representation (TNCQR), a qutrit-based model for encoding RGB digital images in a ternary quantum system. The TNCQR model requires fewer qutrits than the number of qubits needed in equivalent binary models. By incorporating a single ancilla qutrit, the model reduces the depth of high-complexity gates, thereby lowering the overall quantum cost and improving time complexity. To simplify the constructed circuits, an optimization algorithm is presented, consisting of 2 general phases applicable to any image size and one conditional phase specific to each image. This makes TNCQR an efficient, scalable, and resource-optimized quantum image representation model.