J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2025 , Vol. 30 >Issue 5: 998 - 1008

DOI: https://doi.org/10.1007/s12204-023-2662-3

Computing & Computer Technologies

Undecimated Dual-Tree Complex Wavelet Transform and Fuzzy Clustering-Based Sonar Image Denoising Technique

Expand
  • College of Engineering, Dali University, Dali 671003, Yunnan, China

Received date: 2023-03-06

  Accepted date: 2023-06-12

  Online published: 2023-10-24

Fold

Abstract

Imaging sonar devices generate sonar images by receiving echoes from objects, which are often accompanied by severe speckle noise, resulting in image distortion and information loss. Common optical denoising methods do not work well in removing speckle noise from sonar images and may even reduce their visual quality. To address this issue, a sonar image denoising method based on fuzzy clustering and the undecimated dual-tree complex wavelet transform is proposed. This method provides a perfect translation invariance and an improved directional selectivity during image decomposition, leading to richer representation of noise and edges in high frequency coefficients. Fuzzy clustering can separate noise from useful information according to the amplitude characteristics of speckle noise, preserving the latter and achieving the goal of noise removal. Additionally, the low frequency coefficients are smoothed using bilateral filtering to improve the visual quality of the image. To verify the effectiveness of the algorithm, multiple groups of ablation experiments were conducted, and speckle sonar images with different variances were evaluated and compared with existing speckle removal methods in the transform domain. The experimental results show that the proposed method can effectively improve image quality, especially in cases of severe noise, where it still achieves a good denoising performance.

Cite this article

LIU Biao, LIU Guangyu, FENG Wei, WANG Shuai, ZHOU Bao, ZHAO Enming . Undecimated Dual-Tree Complex Wavelet Transform and Fuzzy Clustering-Based Sonar Image Denoising Technique[J]. Journal of Shanghai Jiaotong University(Science), 2025 , 30(5) : 998 -1008 . DOI: 10.1007/s12204-023-2662-3

References

[1] WANG C J, SHEN L R, FAN Y S, et al. Sonar image denoising based on anisotropic guided filtering [C]//2022 5th International Conference on Intelligent Autonomous Systems. Dalian: IEEE, 2022: 54-59.

[2] LIU G Y, ZENG Z Y, CAO Y, et al. Sonar image denoising based on density clustering and gray scale transformation in NSST domain [J]. Journal of Hunan University (Natural Sciences), 2022, 49(8): 186-195 (in Chinese).

[3] LI F, ZHU L L. Comparative research on denoising effects of common filtering algorithms based on sonar image [J]. Mine Warfare & Ship Self-Defence, 2017, 25(4): 82-86 (in Chinese).

[4] CHEN Y, XU H L, XING Q, et al. A denoising algorithm for SICM image based on wavelet and bilateral filtering [J]. Electronic Measurement Technology, 2022, 45(4): 114-119 (in Chinese).

[5] KOLLEM S, REDDY K R, RAO D S. Improved partial differential equation-based total variation approach to non-subsampled contourlet transform for medical image denoising [J]. Multimedia Tools and Applications, 2021, 80(2): 2663-2689.

[6] ROUTRAY S, MALLA P P, SHARMA S K, et al. A new image denoising framework using bilateral filtering based non-subsampled shearlet transform [J]. Optik, 2020, 216: 164903.

[7] WANG L Y, CHEN J Y. Image denoising based on dual tree complex wavelet transform and bilateral filter [J]. Journal of Huazhong Normal University (Natural Sciences), 2021, 55(6): 1030-1036 (in Chinese).

[8]   ZHANG Y L. Improving denoising algorithm for fuzzy clustering-based wavelet transform image [J]. Computer Applications and Software, 2010, 27(8): 133-135 (in Chinese).

[9] KINGSBURY N. The dual-tree complex wavelet transform: A new efficient tool for image restoration and enhancement [C]//9th European Signal Processing Conference. Rhodes: IEEE, 1998: 1-4.

[10] HILL P R, ANANTRASIRICHAI N, ACHIM A, et al. Undecimated dual-tree complex wavelet transforms [J]. Signal Processing: Image Communication, 2015, 35: 61-70.

[11] YANG P, YANG G W. Bivariate shrinkage using undecimated dual-tree complex wavelet transform for image denoising [J]. Journal of Intelligent & Fuzzy Systems, 2016, 30(6): 3111-3122.

[12] WU J N, SHI M H, XING Z. Image denoising using magnitude-phase of the undecimated dual-tree complex wavelet transform [J]. Infrared Technology, 2018, 40(7): 647-653 (in Chinese).

[13] SAEEDZARANDI M, NEZAMABADI-POUR H, SARYAZDI S, et al. Image denoising in undecimated dual-tree complex wavelet domain using multivariate t-distribution [J]. Multimedia Tools and Applications, 2020, 79(31/32): 22447-22471.

[14] FARHADIANI R, HOMAYOUNI S, SAFARI A. Hybrid SAR speckle reduction using complex wavelet shrinkage and non-local PCA-based filtering [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(5): 1489-1496.

[15] HE X W, SUN Y, WEI X, et al. Denoising algorithm of cerenkov luminescence images based on spatial information improved clustering [J]. Acta Optica Sinica, 2018, 38(10): 1017001.

[16] WANG H Q, LÜ J Y, ZHANG W. GPR image denoising based on bilateral filtering BM3D algorithm[J]. Journal of Lanzhou University of Technology, 2022, 48(1): 91-97 (in Chinese).

[17] KARTHIKEYAN M, VIJAYARAGHAVAN V. Denoising of images using principal component analysis and undecimated dual tree complex wavelet transform [J]. International Journal of Biomedical Engineering and Technology, 2018, 26(3/4): 304.

[18] WANG X H, ZHOU Y, ZHOU Y. Infrared and visible image fusion in undecimated dual-tree complex wavelet domain [J]. Computer Engineering and Design, 2017, 38(3): 729-734 (in Chinese).

[19] HUANG Y F, LI W X, YUAN F. Speckle noise reduction in sonar image based on adaptive redundant dictionary [J]. Journal of Marine Science and Engineering, 2020, 8(10): 761.

[20] NIU H Q, WU J Z, XU J, et al. Denoising of infrared images of porcelain sleeve cable terminal considering inter-scale correlation [J]. Journal of South China University of Technology (Natural Science Edition), 2017, 45(4): 15-21 (in Chinese).

[21] TANG W, JIA F X, WANG X M. Adaptive fusion of visible and infrared images based on bilateral filtering [J]. Acta Armamentarii, 2022, 43(11): 2836-2845 (in Chinese).

[22]    XUE S Q, HE D D. Denoising algorithm for medical ultrasound image based on 2D-VMD and bilateral filtering [J]. Journal of Xi’an University of Science and Technology, 2021, 41(3): 516-523 (in Chinese).

[23] KAUR S, SINGH N. Image denoising techniques: a review[J]. International Journal of Innovative Research in Computer and Communication Engineering, 2014, 2(6): 4578-4583.

[24] LIU G Y, BIAN H Y, SHEN Z Y, et al. Research on spectral clustering met algorithm of sonar image denoising in morphological wavelet domain [J]. Transducer and Microsystem Technologies, 2011, 30(10): 41-43 (in Chinese).

[25] BUADES A, COLL B, MOREL J M. A non-local algorithm for image denoising [C]//2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego: IEEE, 2005: 60-65.

Options
Outlines

/

〈 〉