+高级检索
基于密度聚类与灰度变换的NSST域声呐图像去噪
DOI:
作者:
作者单位:

作者简介:

通讯作者:

基金项目:


Sonar Image Denoising Based on Density Clustering and Gray Scale Transformation in NSST Domain
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    传统图像去噪方法在去除声呐图像斑点噪声的同时,难以有效保留细节特征. 针 对该问题,提出一种基于密度聚类与灰度变换的非下采样剪切波域图像去噪方法 . 利用非下 采样剪切波变换将含噪图像分解为高频系数和低频系数,根据声呐图像中斑点噪声的分布特 性,采用基于密度的噪声应用空间聚类(Density-based Spatial Clustering of Applications with Noise,DBSCAN)算法对高频系数进行处理,分离噪声信号,保留细节信息;对低频系数进行灰 度变换,以增强图像对比度. 通过非下采样剪切波逆变换对处理后的高频系数和低频系数进行 重构,实现图像去噪. 实验结果表明,本文方法在改善图像均方误差、峰值信噪比和结构相似度 等指标上效果明显,去噪后图像的视觉效果和边缘保持能力得到较大提升. 随着噪声方差的逐 渐增大,本文方法的优越性得到进一步体现,适用于具有高密度噪声的声呐图像去噪.

    Abstract:

    Traditional image denoising methods are difficult to effectively retain detailed features while filtering the speckle noise of sonar images. To overcome this problem, an image denoising method based on density clustering and grayscale transformation in a non-subsampled shearlet domain is proposed. Non-subsampled shearlet transform is used to decompose the noisy image into high-frequency coefficients and low-frequency coefficients. According to the distribution characteristics of speckle noise in the sonar image, the Density-based Spatial Clustering of Applica? tions with Noise(DBSCAN) algorithm is used to process high-frequency coefficients to separate noise interference and retain detailed information. Gray-scale transformation is performed on the low-frequency coefficients to enhance image contrast. Finally, the processed high-frequency coefficients and low-frequency coefficients are reconstructed by non-subsampled shearlet inverse transformation to achieve image denoising. The experimental results show that the method is effective in improving the image’s mean square error, peak signal-to-noise ratio, structural similarity, and so on. After denoising, the visual effect and edge retention ability of the image are greatly improved. With the gradual increase of the noise variance, the superiority of this method is further manifested, and it is suitable for the denoising of sonar images with high-density noise.

    参考文献
    相似文献
    引证文献
文章指标
  • PDF下载次数:
  • HTML阅读次数:
  • 摘要点击次数:
  • 引用次数:
引用本文

刘光宇 ,曾志勇 ,曹禹 ,赵恩铭 ,邢传玺 .基于密度聚类与灰度变换的NSST域声呐图像去噪[J].湖南大学学报:自然科学版,2022,49(8):186~195

复制
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2022-09-07
  • 出版日期:
版权声明:稿件一经被本刊录用,即视为作者将版权授予本刊,本刊有权根据工作需要,允许合作的数据库、新媒体平台及其他媒体进行二次转载、推介、下载和传播,如有异议,请在来稿中声明。
关闭