Partition Enhancement Method for NSCT Domain of Side-scan Sonar Image

被引:0
|
作者
Wu H. [1 ]
Qiu Z. [1 ]
Zhang W. [1 ]
机构
[1] Unit 91388 of PLA, Zhanjiang
来源
Binggong Xuebao/Acta Armamentarii | 2021年 / 42卷 / 07期
关键词
Coefficient difference; Non-subsampled contourlet transform; Partition enhancement; Side-scan sonar;
D O I
10.3969/j.issn.1000-1093.2021.07.014
中图分类号
学科分类号
摘要
The serious noise pollution, low contrast of gray values of target and background areas, and weak edges in the side-scan sonar image are due to the limitations of side-scan sonar imaging mechanism and the abundant noise sources in the ocean. In response to the above problems, a partition enhancement method for the non-subsampled contourlet transform (NSCT) domain of side-scan sonar images is proposed. For the low-frequency part of sonar image, a nonlinear function enhancement method is used to improve the contrast of low-frequency image. For the high-frequency part of sonar image, the noise and texture edges are partitioned and the corresponding processing is made by analyzing the distribution rule of the difference between the maximum and minimum values of sub-band coefficients in different directions on the same scale. The proposed method was compared with the gamma enhancement method and the wavelet threshold enhancement method through experiment. The results show that the proposed method not only denoises noise well, but also can suppresses trivial textures and enhances weak edges. The enhancement effect for side-scan sonar image is more prominent. © 2021, Editorial Board of Acta Armamentarii. All right reserved.
引用
收藏
页码:1463 / 1470
页数:7
相关论文
共 13 条
  • [1] LI H B, TENG H Z, SONG H Y, Et al., Technology on the extraction of seabed target based on high resolution side-scan sonar[J], Hydrographic Surveyng and Charting, 30, 6, pp. 71-73, (2010)
  • [2] ZHANG L, ZHU Z D., A novel nonlinear method for image enhancement based on nonsubsampled contourlet transform, Journal of Electronics & Information Technology, 31, 8, pp. 1786-1790, (2009)
  • [3] XING S X, XIAO H B, CHEN T H, Et al., Study of image fusion technology based on object extraction and NSCT, Journal of Optoelectronics•Laser, 24, 3, pp. 583-588, (2013)
  • [4] WU Y Q, WU C., Denoising of hyperspectral remote sensing images using NSCT and KPCA, Journal of Remote Sensing, 16, 3, pp. 533-544, (2012)
  • [5] ZHOU Y, LI Q W, HUO G Y., Adaptive image enhancement based on NSCT coefficient histogram matching, Optics and Precision Engineering, 22, 8, pp. 2214-2222, (2014)
  • [6] JIA J, JIAO L C, XIANG H L., Using bivariate threshold function for image denoising in NSCT domain, Journal of Electronics & Information Technology, 31, 3, pp. 532-536, (2009)
  • [7] LI Q W, MA G C, HUO G Y, Et al., New segmentation method of side-scan sonar image based on edge detection in NSCT domain, Chinese Journal of Scientific Instrument, 34, 8, pp. 1795-1801, (2013)
  • [8] ZHANG Q, GUO B., Multifocus image fusion using the nonsubsampled contourlet transform, Signal Processing, 89, 7, pp. 1334-1346, (2009)
  • [9] WU H L, XU H P, WANG P B, Et al., Denoising method based on intrascale correlation in non subsampled contourlet transform for synthetic aperture radar images[J], Journal of Applied Remote Sensing, 13, 4, pp. 1232-1235, (2019)
  • [10] DABOV K, FOI A, KATKOVNIK V, Et al., Image denoising by sparse 3D transform-domain collaborative filtering, IEEE Transactions on Image Processing, 16, 8, pp. 2080-2095, (2007)