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Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment

机译:量子图像处理及其在边缘检测中的应用:理论与实验

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摘要

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.
机译:数字图像的处理不断增加体积和相关性,并伴随数据存储,传输和处理能力。在量子 - 机械系统中编码图像信息而不是经典的图像信息,并且用量子信息处理替换经典可能会减轻这些挑战中的一些挑战。通过在量子机械系统中的编码和处理图像信息,我们在这里演示了量子图像处理的框架,其中纯量子状态对图像信息进行编码:我们在计算基础上编码概率幅度和像素位置中的像素值状态。与现有实现相比,我们的量子图像表示减少了所需数量的Qubits,并且我们提供了在其经典对应上提供指数加速的图像处理算法。对于检测图像边缘的常用任务,我们提出并实现了一个量子算法,该量子算法只完成了一个单QUBit操作,与图像的大小无关。这证明了在大数据时代中高效图像和视频处理的量子图像处理的潜力。

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