Robust image denoising for sonar imagery

Avi Abu, Roee Diamant

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The recent boost in undersea operations has led to the development of high-resolution sonar systems mounted on autonomous vehicles, and aimed to scan the sea floor and detect objects. An important part of sonar detection is the image denoising, where the background is smoothed and noise components are removed while preserving the object’s borders. Sonar image denoising is a challenging task, mostly due to the heavy intensity inhomogeneity of the background and the heavy spatial varying background. In this paper, we propose an algorithm for sonar image denoising that is based on the adaptation of the nonlocal means-based filter. The noise in the highlight and background regions is modeled by the exponential distribution, while the noise in the shadow region is modeled by the Gaussian distribution. We estimate the label of each pixel through image segmentation to estimate the parameters of each distribution. Then, the minimum entropy criteria is used to decide which statistics model in the denoising filter gives the best results. Results for synthetic sonar images and over real sonar images demonstrate that the proposed method successfully removes the noise components while preserving the object’s edges.

Original languageEnglish
Title of host publication2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538616543
StatePublished - 4 Dec 2018
Event2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 - Kobe, Japan
Duration: 28 May 201831 May 2018

Publication series

Name2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018


Conference2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.


  • Image enhancement
  • NL Means-based denoising
  • Sonar signal processing
  • Speckle filter

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Oceanography
  • Space and Planetary Science
  • Energy Engineering and Power Technology
  • Ocean Engineering
  • Acoustics and Ultrasonics
  • Instrumentation


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