Wavelet threshold image denoising method based on F-type double-chain quantum genetic algorithm

A quantum genetic algorithm, wavelet threshold technology, applied in image enhancement, image data processing, computing and other directions, can solve problems such as unscientific

Active Publication Date: 2015-11-18
HARBIN ENG UNIV
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  • Wavelet threshold image denoising method based on F-type double-chain quantum genetic algorithm
  • Wavelet threshold image denoising method based on F-type double-chain quantum genetic algorithm
  • Wavelet threshold image denoising method based on F-type double-chain quantum genetic algorithm

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[0055] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0056]The present invention aims at the defect of above-mentioned background technology, on the basis of DCQGA (double-chain quantum genetic algorithm), improves its coding, chromosome revolving door update and variation process, and then proposes a kind of high-density search space, self-adaptive update Step-size F-type double-chain quantum genetic algorithm (FDoubleChainsQuantumGeneticAlgorithm, F_DCQGA). And introduce it into the field of wavelet image denoising.

[0057] At the same time, when determining the wavelet threshold, it is considered that the maximum value of the j+1th layer wavelet expansion coefficient corresponding to the noise in each layer is smaller than the maximum value of the jth layer wavelet expansion coefficient Based on the characteristics of multiplier, a set of thresholds can be automatically adjusted according to the character...

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Abstract

The invention discloses a wavelet threshold image denoising method based on an F-type double-chain quantum genetic algorithm. First of all, single-value mapping processing is performed on a coding space, the search space of the algorithm is reduced, and search density is increased; secondly, a self-adaptive step length factor is introduced during quantum updating to enable a step length to change along with the gradient change of a target function at a search point so that the problem of global optimal solution search difficulty caused by an "oscillation" phenomenon generally existing in a conventional searching optimization algorithm at present is effectively solved; and finally, a pi/6 gate is brought forward during chromosome variation updating so that the disadvantage is improved that conventional NOT gate variation cannot update quantum bit probability amplitude. According to the invention, an F_DCQGA optimization algorithm is also applied to a threshold selection mechanism of wavelet threshold de noising, at the same time, a self-adaptive threshold function is brought forward, and accordingly, a conventional wavelet threshold denoising method is improved. The method provided by the invention improves the convergence speed and the search precision of a wavelet threshold function.

Description

technical field [0001] The invention belongs to the field of quantum computing and image denoising, in particular to a wavelet threshold image denoising method based on F-type double-chain quantum genetic algorithm. Background technique [0002] The concept of quantum computing was proposed by physicist Feynman in 1982. Its main idea is to use the characteristics of entanglement, superposition and coherence of microscopic particles (quantum) to solve NP problems that cannot be solved in classical computing. Later, Peter Shor and Grover respectively proposed the quantum algorithm and quantum search algorithm for decomposing the prime factors of large numbers, which injected new vitality into the research of quantum computing and triggered an upsurge of quantum computing research. Quantum's outstanding parallel computing ability has been applied to various optimization algorithms. Quantum Genetic Algorithm (QGA) has the advantages of small population size, strong search abilit...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 国强戚连刚孙宇枭万建
Owner HARBIN ENG UNIV
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