北京化工大学学报(自然科学版)2024,Vol.51Issue(1) :128-134.DOI:10.13543/j.bhxbzr.2024.01.015

一种具有随机单向变异的基于小波框架的奇点集检测图像去噪算法

An image denoising algorithm for singularity set detection based on a wavelet frame with random unidirectional variation

王鸿 崔丽鸿 孙海禄
北京化工大学学报(自然科学版)2024,Vol.51Issue(1) :128-134.DOI:10.13543/j.bhxbzr.2024.01.015

一种具有随机单向变异的基于小波框架的奇点集检测图像去噪算法

An image denoising algorithm for singularity set detection based on a wavelet frame with random unidirectional variation

王鸿 1崔丽鸿 1孙海禄2
扫码查看

作者信息

  • 1. 北京化工大学 数理学院,北京 100029
  • 2. 河北地质大学 信息工程学院,石家庄 050031
  • 折叠

摘要

在图像恢复过程中,奇点集检测结果的准确性很大程度上会受到噪声的干扰,并且在其检测的迭代过程中易陷入局部最优.利用随机全局搜索的思想,借鉴遗传算法的变异操作,提出一种基于小波框架的具有随机单向变异操作的奇点集检测图像去噪算法,在保证图像恢复效果的同时,极大缩短了运算时间.最后通过实验验证了该算法的有效性.

Abstract

In an image restoration process,the detection of a singularity set will significantly affect the accuracy of the results due to the interference of noise,and it is easy to fall into a local optimum during the iterative detection process.In this paper,an image denoising algorithm for singularity set detection based on a wavelet frame with ran-dom unidirectional variation is proposed based on the idea of random global search and the mutation operation of ge-netic algorithm.The operation time can be greatly shortened,while image recovery effect is maintained.Finally,the effectiveness of the algorithm is verified by experiments.

关键词

图像恢复/奇点集检测/随机全局搜索/单向变异/小波框架

Key words

image restoration/singularity set detection/random global search/unidirectional variation/wavelet frame

引用本文复制引用

出版年

2024
北京化工大学学报(自然科学版)
北京化工大学

北京化工大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.399
ISSN:1671-4628
参考文献量2
段落导航相关论文