Abstract
Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission and processing power. Encoding the image information in quantum-mechanical systems instead of classical ones and replacing classical with quantum information processing may alleviate some of these challenges. By encoding and processing the image information in quantum-mechanical systems, we here demonstrate the framework of quantum image processing, where a pure quantum state encodes the image information: we encode the pixel values in the probability amplitudes and the pixel positions in the computational basis states. Our quantum image representation reduces the required number of qubits compared to existing implementations, and we present image processing algorithms that provide exponential speed-up over their classical counterparts. For the commonly used task of detecting the edge of an image, we propose and implement a quantum algorithm that completes the task with only one single-qubit operation, independent of the size of the image. This demonstrates the potential of quantum image processing for highly efficient image and video processing in the big data era.
Highlights
Vision is by far the most important channel for obtaining information
We demonstrate the basic framework of quantum image processing based on a different type of quantum image representation (QImR), which reduces the qubit resources required for encoding an image
II, we firstly introduce the basic framework of quantum image processing, present the experimental demonstration for several basic image transforms on a nuclear magnetic resonance (NMR) quantum information processor
Summary
Vision is by far the most important channel for obtaining information. the analysis of visual information. The analysis of visual information by electronic devices has become a reality that enables machines to directly process and analyze the information contained in images and stereograms or video streams, resulting in rapidly expanding applications in widely separated fields like biomedicine, economics, entertainment, and industry (e.g., automatic pilot) [5,6,7] Some of these tasks can be performed very efficiently by digital data processors, but. We propose a highly efficient quantum algorithm for detecting the boundary between different regions of a picture: It requires only one single-qubit gate in the processing stage, independent of the size of the picture We perform both numerical and experimental demonstrations to prove the validity of our quantum edge detection algorithm. IV, we summarize the results and give a perspective for future work
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