Quantum Overflow Detection for Reliable Bioinspired Image Enhancement
Neeraj Kumar Misra, Nirupma Pathak · IEEE Access · 2026
In quantum information science, fundamental principles of quantum mechanics, particularly quantum parallelism are leveraged to enable computational capabilities that exceed the performance limits of classical computing systems. This paper proposes a novel overflow detection circuit (ODC) within a Binary-Coded Decimal (BCD) framework, aimed at improving biomedical image enhancement. In this research, quantum-inspired methodologies for biomedical image enhancement have not been extensively investigated. The proposed ODC quantum circuit is transpiler and executed on Ibm_Kingston quantum hardware, where measured qubit frequencies are compared with ideal simulation results to characterize hardware-induced errors. The ODC circuit is decomposed into a Clifford+T gate set, and a noise-aware Quantum Equivalent Design (QED) is developed within the IBM Quantum Experience platform. Various quantum noise models, including depolarizing, amplitude damping, phase damping, and bit-flip noise, are quantitatively analyzed using the core IBM Qiskit Ignis framework. The real-time biomedical images enhancement performed by ODC circuit with the help of code simulated on IBM-Qiskit. A case study is conducted to demonstrate the effectiveness of the proposed overflow detection approach in biomedical imaging applications. Circuit testability is rigorously evaluated through missing-target-gate fault simulations. Comparative analysis indicates that the proposed ODC achieves a 66.66% reduction in gate count, a 33.33% reduction in garbage outputs, a 66.66% reduction in ancilla inputs, and a 50% reduction in quantum cost. These findings underscore the efficiency, robustness, and practical viability of the proposed quantum ODC for quantum-enhanced biomedical imaging and noise-resilient quantum information processing systems.