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Improved quantum image weighted average filtering algorithm
by
Deng, Jermiah D.
, Qing, Xianrong
, Yuan, Suzhen
, Yinxia, Shu
, Li, Xianli
in
Algorithms
/ Color imagery
/ Complexity
/ Data Structures and Information Theory
/ Fourier transforms
/ Image filters
/ Image processing
/ Mathematical Physics
/ Modules
/ Physics
/ Physics and Astronomy
/ Quantum Computing
/ Quantum Information Technology
/ Quantum Physics
/ Spintronics
2025
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Improved quantum image weighted average filtering algorithm
by
Deng, Jermiah D.
, Qing, Xianrong
, Yuan, Suzhen
, Yinxia, Shu
, Li, Xianli
in
Algorithms
/ Color imagery
/ Complexity
/ Data Structures and Information Theory
/ Fourier transforms
/ Image filters
/ Image processing
/ Mathematical Physics
/ Modules
/ Physics
/ Physics and Astronomy
/ Quantum Computing
/ Quantum Information Technology
/ Quantum Physics
/ Spintronics
2025
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Do you wish to request the book?
Improved quantum image weighted average filtering algorithm
by
Deng, Jermiah D.
, Qing, Xianrong
, Yuan, Suzhen
, Yinxia, Shu
, Li, Xianli
in
Algorithms
/ Color imagery
/ Complexity
/ Data Structures and Information Theory
/ Fourier transforms
/ Image filters
/ Image processing
/ Mathematical Physics
/ Modules
/ Physics
/ Physics and Astronomy
/ Quantum Computing
/ Quantum Information Technology
/ Quantum Physics
/ Spintronics
2025
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Improved quantum image weighted average filtering algorithm
Journal Article
Improved quantum image weighted average filtering algorithm
2025
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Overview
Average filtering plays a vital role in image smoothing tasks. However, existing quantum image weighted average filtering methods suffer from high circuit complexity. Therefore, this paper proposes an improved quantum color image weighted average filtering algorithm and its corresponding quantum circuit. First, we improve the quantum circuit to prepare classical color images into a quantum state. Then, an improved quantum divider is developed, and a weighted average filter is constructed using basic quantum image processing modules. Next, to enhance the universality of the filter, a quantum comparator with lower circuit complexity is used to design a noise detection module for distinguishing noise from real signals. Finally, a quantum circuit for color image weighted average filtering is designed, and simulations are conducted on the IBM Quantum Experience (IBM Q) platform to verify the feasibility of our algorithm. The analysis shows that compared with existing methods, this method significantly reduces the circuit complexity and has better filtering performance.
Publisher
Springer US,Springer Nature B.V
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