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Algorithms · Quantum image processing

Quantum edge detection on an amplitude-encoded image

Detect the edges of a digital image: the pixel positions at which the image values change sharply. Processing digital images keeps growing in volume, with matching demands on data storage, transmission and processing power.

Attested & literatureUpdated

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  • Record typeLiterature reference
  • Reference implementationquantum_hadamard_edge_detection
  • Reported costOne single-qubit operation for the edge-detection step, independent of the size of the image; for the image processing algorithms the paper presents, an exponential speed-up over their classical counterparts. The qubit claim is comparative rather than absolute — the representation reduces the required number of qubits compared to existing implementations — and the abstract states no gate count for preparing the encoded image or for reading the result back out.
  • Papers1

Quantum vs classical

Classical baseline

Compare Quantum image processing with the strongest classical method for the same instance, input budget, and output metric.

Quantum claim

This reference exposes a quantum circuit pattern; it does not imply an application-level speedup without a matched benchmark.

How to compare

Report input loading, circuit depth, repetitions, classical preprocessing, post-processing, and wall-clock time together.

References

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

    Xi-Wei Yao, Hengyan Wang, Zeyang Liao, Ming-Cheng Chen, Jian Pan, Jun Li, Kechao Zhang, Xingcheng Lin, Zhehui Wang, Zhihuang Luo, Wenqiang Zheng, Jianzhong Li, Meisheng Zhao, Xinhua Peng, Dieter Suter · 2018

    Primary source. It sets out the quantum image representation this record describes — pixel values in the probability amplitudes, pixel positions in the computational basis states — claims a reduced qubit requirement against existing implementations and an exponential speed-up for the image processing algorithms it presents, and reports the edge-detection algorithm as both proposed and implemented, completing the task with one single-qubit operation independent of image size. Consult it for the state-preparation and readout procedures, for which single-qubit operation is used, and for the experiment's platform, image sizes and accuracy, none of which the abstract states.

Attested & literature
  • Peer-reviewed paper
Method
Curation only. This record documents the algorithm a published reference implementation demonstrates, not the demonstration itself: nothing in Leona runs Qmod. The primary reference's title, authors and submission year were read from its arXiv abs page, and the complexity claim taken from a clause of that paper's abstract (abstract of arXiv:1801.01465: "we propose and implement a quantum algorithm that completes the task with only one single-qubit operation, independent of the size of the image"; the speed-up clause is "we present image processing algorithms that provide exponential speed-up over their classical counterparts"; the qubit clause is "Our quantum image representation reduces the required number of qubits compared to existing implementations". That abstract states no running time, gate count, circuit depth or error bound, and the demonstration this record covers states no bound of any kind either.). No circuit was constructed, simulated or run.
Result
Pass · the record's problem statement and primary reference agree with the sources named above.
Caveat
This is a literature record: nothing was built, compiled, simulated or run for it, and no image was processed here. It documents the algorithm a published reference implementation demonstrates and does not reproduce that demonstration; nothing in Leona runs Qmod, and the record carries no detail about what that implementation's file contains. The one single-qubit operation is quoted for the edge-detection step: the abstract states no cost for preparing the amplitude-encoded state from a classical image, for the measurements needed to read an edge map back out, or for classical post-processing, and a readout that must recover per-pixel information is where an advantage held inside the register can be lost. The exponential speed-up is asserted for the image processing algorithms the paper presents, against their classical counterparts, with no complexity expression, constant factor or error model given. The abstract does not name which single-qubit operation the algorithm uses, and this record does not supply one from any other source. The experiment is the paper's own report and was not checked here; the abstract states no hardware platform, no image size, and no accuracy achieved.
Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment ↗
Kind
curated reference
Reviewed by
Leona Quantum curation pass
License
Citation metadata only; source publication terms apply
image processingedge detectionamplitude encodingsingle-qubit operation

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