Quality assessment of synthetic aperture sonar images

Debes, Christian; Engel, Robert; Zoubir, Abdelhak M.; Kraft, Arne

doi:10.1109/oceanse.2009.5278181

Cited by 8 publications

(3 citation statements)

References 4 publications

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“…In order to assess the image quality and to detect motion errors, the authors in [8] propose to investigate the energy in the high frequency region of a SAS image. Since the typical configuration of a sonar is rather given by a multiple-receiver array, we adapt this idea by comparing the energy of high frequency regions of coherently combined images with the one of a single ping image.…”

Section: Image Quality Metricmentioning

confidence: 99%

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Quality assessment of synthetic aperture sonar images based on a single ping reference

Leier

Zoubir

2011

OCEANS 2011 IEEE - Spain

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The formation of high resolution Synthetic Aperture Sonar (SAS) images requires precise position information of sensors over the whole synthetic aperture in order to coherently combine the reverberated signals. Due to an insufficient accuracy of the on-board navigation system additional means are necessitated. The state-of-the-art approach is to exploit the correlation structure of received echoes of overlapping phase centers between succeeding pings. This is well-known as the Displaced Phase Center Antenna (DPCA) or Redundant Phase Center (RPC) algorithm. We propose to use a quality metric to recursively assess the reconstructed images against a single ping reference image. This approach obtains a focused image with the maximum resolution by automatically selecting the maximum number of consecutive pings for which unwanted motion has completely been compensated.

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Section: Image Quality Metricmentioning

confidence: 99%

“…As an increase of energy over R suggests the presence of navigation errors [8], the metric is larger than one in case of uncompensated motion errors at ping p 0 + q. The detection of motion errors allows either to stop the reconstruction process or to apply additional motion compensation techniques, e.g.…”

Section: Image Quality Metricmentioning

confidence: 99%

Quality assessment of synthetic aperture sonar images based on a single ping reference

Leier

Zoubir

2011

OCEANS 2011 IEEE - Spain

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“…The SAS image that performs well at adapting the route of a sonar-equipped autonomous underwater vehicle is considered to have sufficient quality. In this case, the measurements of sonar-platform motion, environmental characteristics and the degree of navigation errors have been employed to represent the utility quality of SAS images [14,15]. In [16], some low-level features are correlated with the utility quality of forward looking sonar (FLS) images.…”

Section: Introductionmentioning

confidence: 99%

A blind contour‐aware quality model for sonar images

Chen

Lin

Zhang

et al. 2021

IET Image Processing

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Since the penetration depth of visible light is limited in muddy and dark deep marine environment, sonar imaging, which is independent of natural light, has been attracting much attention in underwater detections. However, the visual quality of sonar image is inevitably damaged during the acquisition and the transmission in the sophisticated and dynamic underwater environment. The quality decrease can further bring negative impacts on oceanic information analysis. To measure the quality decrease of sonar images, this paper proposes a contour-aware model for sonar image quality assessment (CaMSIQA). The CaMSIQA metric is established upon the conclusion that the quality of sonar images can be defined as a measure of their utilities in real application scenarios. We exploit a contour information statistic (CIS) model that is critical to object recognition of sonar images here. Quantifying the changes of the CIS model between the unimpaired and test sonar images makes it possible to perceive the quality decrease of sonar images. Extensive experimental results have demonstrated the effectiveness of the proposed method compared with current mainstream image quality assessment (IQA) methods without full reference information.

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Introduction

Liu

Zhou

2022

Quality Assessment of Visual Content

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Quality assessment of synthetic aperture sonar images

Cited by 8 publications

References 4 publications

Quality assessment of synthetic aperture sonar images based on a single ping reference

Quality assessment of synthetic aperture sonar images based on a single ping reference

A blind contour‐aware quality model for sonar images

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