Achieving quantum advantages for image filtering
- URL: http://arxiv.org/abs/2306.07251v2
- Date: Fri, 28 Jul 2023 20:35:42 GMT
- Title: Achieving quantum advantages for image filtering
- Authors: Zidong Cui and Shan Jin and Akira Sone and Xiaoting Wang
- Abstract summary: We show that for images with efficient encoding and a lower bound on the signal-to-noise ratio, a quantum filtering algorithm can be constructed.
Our work provides insights into the types of images that can achieve a substantial quantum speedup.
- Score: 0.3441021278275805
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Image processing is a fascinating field for exploring quantum algorithms.
However, achieving quantum speedups turns out to be a significant challenge. In
this work, we focus on image filtering to identify a class of images that can
achieve a substantial speedup. We show that for images with efficient encoding
and a lower bound on the signal-to-noise ratio, a quantum filtering algorithm
can be constructed with a polynomial complexity in terms of the qubit number.
Our algorithm combines the quantum Fourier transform with the amplitude
amplification technique. To demonstrate the advantages of our approach, we
apply it to three typical filtering problems. We highlight the importance of
efficient encoding by illustrating that for images that cannot be efficiently
encoded, the quantum advantage will diminish. Our work provides insights into
the types of images that can achieve a substantial quantum speedup.
Related papers
- Deep learning as a tool for quantum error reduction in quantum image
processing [0.0]
We report the successful use of a generative adversarial network trained for image-to-image translation, in conjunction with Phase Unraveling error reduction method, for reducing overall error in images encoded using LPIQE.
Despite the limited availability and quantum volume of quantum computers, quantum image representation is a widely researched area.
arXiv Detail & Related papers (2023-11-08T10:14:50Z) - Tensor Network Based Efficient Quantum Data Loading of Images [0.0]
We present a novel method for creating quantum states that approximately encode images as amplitudes.
We experimentally demonstrate our technique on 8 qubits of a trapped ion quantum computer for complex images of road scenes.
arXiv Detail & Related papers (2023-10-09T17:40:41Z) - Hybrid quantum transfer learning for crack image classification on NISQ
hardware [62.997667081978825]
We present an application of quantum transfer learning for detecting cracks in gray value images.
We compare the performance and training time of PennyLane's standard qubits with IBM's qasm_simulator and real backends.
arXiv Detail & Related papers (2023-07-31T14:45:29Z) - Quantum Fourier Transform for Image Processing [3.4268116130770565]
We propose a quantum algorithm for processing information, such as one-dimensional time series and two-dimensional images, in the frequency domain.
The proposed techniques are implemented on the IBM Qiskit quantum simulator.
arXiv Detail & Related papers (2023-05-10T07:47:37Z) - Entanglement and coherence in Bernstein-Vazirani algorithm [58.720142291102135]
Bernstein-Vazirani algorithm allows one to determine a bit string encoded into an oracle.
We analyze in detail the quantum resources in the Bernstein-Vazirani algorithm.
We show that in the absence of entanglement, the performance of the algorithm is directly related to the amount of quantum coherence in the initial state.
arXiv Detail & Related papers (2022-05-26T20:32:36Z) - A hybrid quantum image edge detector for the NISQ era [62.997667081978825]
We propose a hybrid method for quantum edge detection based on the idea of a quantum artificial neuron.
Our method can be practically implemented on quantum computers, especially on those of the current noisy intermediate-scale quantum era.
arXiv Detail & Related papers (2022-03-22T22:02:09Z) - Improved FRQI on superconducting processors and its restrictions in the
NISQ era [62.997667081978825]
We study the feasibility of the Flexible Representation of Quantum Images (FRQI)
We also check experimentally what is the limit in the current noisy intermediate-scale quantum era.
We propose a method for simplifying the circuits needed for the FRQI.
arXiv Detail & Related papers (2021-10-29T10:42:43Z) - Variational Quantum Optimization with Multi-Basis Encodings [62.72309460291971]
We introduce a new variational quantum algorithm that benefits from two innovations: multi-basis graph complexity and nonlinear activation functions.
Our results in increased optimization performance, two increase in effective landscapes and a reduction in measurement progress.
arXiv Detail & Related papers (2021-06-24T20:16:02Z) - Quantum walk processes in quantum devices [55.41644538483948]
We study how to represent quantum walk on a graph as a quantum circuit.
Our approach paves way for the efficient implementation of quantum walks algorithms on quantum computers.
arXiv Detail & Related papers (2020-12-28T18:04:16Z) - A Quantum Edge Detection Algorithm [2.639737913330821]
We show how, by taking advantage of quantum properties like entanglement and superposition, many image processing algorithms could have an exponential speed-up.
We propose an improved version of a quantum edge detection algorithm.
arXiv Detail & Related papers (2020-12-20T22:10:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.