Image processing involves a variety of tasks such as format conversion, enhancement, pattern recognition, object and face detection, medical and environmental analysis, restoration, and resolution improvement. Maintaining data integrity during image transmission or storage is essential, and Hamming codes are widely used for detecting and correcting errors. Quantum-dot cellular automata (QCA) technology allows the design of nanoscale digital circuits that are low-power, compact, and fast. In this study, we present an efficient QCA-based architecture for implementing Hamming encoders and decoders. This proposed design offers a robust solution for error correction in nanoscale digital systems, demonstrating significant potential for applications where data integrity is critical, such as digital image processing. Our evaluation, conducted using QCADesigner, shows that the developed system achieves a 45.31% improvement in performance and uses 74.96% fewer cells compared to conventional architectures, highlighting its effectiveness and suitability for future nanoscale communication and image processing applications.
Liang Li (Wed,) studied this question.