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Non-homogeneous noise removal for side scan sonar images using a structural sparsity based compressive sensing algorithm

구조적 희소성 기반 압축 센싱 알고리즘을 통한 측면주사소나 영상의 비균일 잡음 제거

Youngseng Chen1
,
Bonwha Ku1
,
Seungho Lee2
,
Seongil Kim2
,
Hanseok Ko1*
진 영생1
,
구 본화1
,
이 승호2
,
김 성일2
,
고 한석1*
1Engineering Building Room 419, Department of Electronics and Computer Engineering, Korea University Anam Campus
1고려대학교
2국방과학연구소
*교신저자. *Corresponding Author. 
31 January 2018. pp. 73-81
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Abstract

The quality of side scan sonar images is determined by the frequency of a sonar. A side scan sonar with a low frequency creates low-quality images. One of the factors that lead to low quality is a high-level noise. The noise is occurred by the underwater environment such as equipment noise, signal interference and so on. In addition, in order to compensate for the transmission loss of sonar signals, the received signal is recovered by TVG (Time-Varied Gain), and consequently the side scan sonar images contain non-homogeneous noise which is opposite to optic images whose noise is assumed as homogeneous noise. In this paper, the SSCS (Structural Sparsity based Compressive Sensing) is proposed for removing non-homogeneous noise. The algorithm incorporates both local and non-local models in a structural feature domain so that it guarantees the sparsity and enhances the property of non-local self-similarity. Moreover, the non-local model is corrected in consideration of non-homogeneity of noises. Various experimental results show that the proposed algorithm is superior to existing method.

Keywords
Side scan sonar
Denoise
Compressive sensing
Structural feature

측면주사소나 영상의 화질은 소나 운용 주파수의 영향을 받는다. 저주파 측면주사소나 장비로 얻는 영상은 저화질 영상이며, 잡음이 화질 저하의 요소 중 하나가 된다. 균일한 잡음을 가정하는 광학 영상과는 달리. 측면주사소나 데이터의 잡음은 해양 환경(장비 소음, 신호 간섭 등)에 의해 발생한다. 또한 소나 신호의 전달 손실을 보상하고자 시간변환이득(Time-Varied Gain, TVG)을 수행하며, 이로 인해 측면주사소나 영상에 비균일 잡음이 생성된다. 본 논문에서는 측면주사소나 영상에 포함된 비균일 잡음을 제거하는 구조적 희소성에 기반한 압축 센싱 알고리즘 (Structural Sparsity based Compressive Sensing, SSCS)을 제안한다. 영상의 구조적 특징 도메인에서 국부적 및 비국부적 모델링을 동시에 구현하여 계수의 희소성을 보장하면서 비국부적 자가 유사성을 강화한다. 그리고 잡음의 비균일성을 고려하여 비국부적 모델링을 보상한다. 다양한 모의 실험을 통해 제안한 알고리즘의 우수성을 입증한다.

키워드
측면 주사 소나
잡음 제거
압축센싱
구조적 특징
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Information
  • Publisher :The Acoustical Society of Korea
  • Publisher(Ko) :한국음향학회
  • Journal Title :The Journal of the Acoustical Society of Korea
  • Journal Title(Ko) :한국음향학회지
  • Volume : 37
  • No :1
  • Pages :73-81
  • Received Date : 2017-12-11
  • Revised Date : 2018-01-05
  • Accepted Date : 2018-01-30
  • DOI :https://doi.org/10.7776/ASK.2018.37.1.073
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