Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission

N. Mirizzi, Shahriar Negahdaripour, C. Guaragnella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The traditional navigation cameras are being replaced by 2-D forward-scan sonar video devices, when untethered submersible robots operate in underwater environments with poor visibility. A typical FS sonar image comprises of object highlight and cast shadow regions, as well as large relatively uniform background areas, generally corrupted with high level of speckle noise. While both are important in image analysis for object and scene interpretation, highlight and shadow regions encode valuable information for inferring 3-D shape. For some tasks, real-time man-machine interaction and cooperation can significantly enhance the robot performance. The transmission of live video from the robotic platform to a remote surface station requires high video compression ratios to meet the current low-bandwidth limitations of acoustic channels. This work makes use of a novel forward-scan sonar image coding scheme, where 1) object highlights and shadow edges (treated as foreground) are segmented from the less informative background, maintaining high details for encoding; 2) background is highly compressed to transmit at very little cost; 3) together, they are decoded at the receiver end for reconstruction. Application to various video sequences shows an average compression ratio of 100, for raw video data at 512×96 resolution transmitted at 10 frame per second.

Original languageEnglish (US)
Title of host publicationOCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538648148
DOIs
StatePublished - Jan 7 2019
EventOCEANS 2018 MTS/IEEE Charleston, OCEANS 2018 - Charleston, United States
Duration: Oct 22 2018Oct 25 2018

Publication series

NameOCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

Conference

ConferenceOCEANS 2018 MTS/IEEE Charleston, OCEANS 2018
CountryUnited States
CityCharleston
Period10/22/1810/25/18

Fingerprint

Sonar
sonar
Image coding
Robots
modeling
Human computer interaction
Speckle
Image compression
Visibility
Image analysis
compression
underwater environment
Navigation
Robotics
Acoustics
Cameras
speckle
Bandwidth
submersible
robotics

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Oceanography

Cite this

Mirizzi, N., Negahdaripour, S., & Guaragnella, C. (2019). Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission. In OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018 [8604666] (OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/OCEANS.2018.8604666

Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission. / Mirizzi, N.; Negahdaripour, Shahriar; Guaragnella, C.

OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8604666 (OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mirizzi, N, Negahdaripour, S & Guaragnella, C 2019, Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission. in OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018., 8604666, OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018, Institute of Electrical and Electronics Engineers Inc., OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018, Charleston, United States, 10/22/18. https://doi.org/10.1109/OCEANS.2018.8604666
Mirizzi N, Negahdaripour S, Guaragnella C. Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission. In OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018. Institute of Electrical and Electronics Engineers Inc. 2019. 8604666. (OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018). https://doi.org/10.1109/OCEANS.2018.8604666
Mirizzi, N. ; Negahdaripour, Shahriar ; Guaragnella, C. / Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission. OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018. Institute of Electrical and Electronics Engineers Inc., 2019. (OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018).
@inproceedings{7713ae8af580422e9294f65b0af5faf9,
title = "Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission",
abstract = "The traditional navigation cameras are being replaced by 2-D forward-scan sonar video devices, when untethered submersible robots operate in underwater environments with poor visibility. A typical FS sonar image comprises of object highlight and cast shadow regions, as well as large relatively uniform background areas, generally corrupted with high level of speckle noise. While both are important in image analysis for object and scene interpretation, highlight and shadow regions encode valuable information for inferring 3-D shape. For some tasks, real-time man-machine interaction and cooperation can significantly enhance the robot performance. The transmission of live video from the robotic platform to a remote surface station requires high video compression ratios to meet the current low-bandwidth limitations of acoustic channels. This work makes use of a novel forward-scan sonar image coding scheme, where 1) object highlights and shadow edges (treated as foreground) are segmented from the less informative background, maintaining high details for encoding; 2) background is highly compressed to transmit at very little cost; 3) together, they are decoded at the receiver end for reconstruction. Application to various video sequences shows an average compression ratio of 100, for raw video data at 512×96 resolution transmitted at 10 frame per second.",
author = "N. Mirizzi and Shahriar Negahdaripour and C. Guaragnella",
year = "2019",
month = "1",
day = "7",
doi = "10.1109/OCEANS.2018.8604666",
language = "English (US)",
series = "OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018",

}

TY - GEN

T1 - Underwater Forward-Scan Sonar Video Coding by Background Modeling and Synthesis for Real-Time Transmission

AU - Mirizzi, N.

AU - Negahdaripour, Shahriar

AU - Guaragnella, C.

PY - 2019/1/7

Y1 - 2019/1/7

N2 - The traditional navigation cameras are being replaced by 2-D forward-scan sonar video devices, when untethered submersible robots operate in underwater environments with poor visibility. A typical FS sonar image comprises of object highlight and cast shadow regions, as well as large relatively uniform background areas, generally corrupted with high level of speckle noise. While both are important in image analysis for object and scene interpretation, highlight and shadow regions encode valuable information for inferring 3-D shape. For some tasks, real-time man-machine interaction and cooperation can significantly enhance the robot performance. The transmission of live video from the robotic platform to a remote surface station requires high video compression ratios to meet the current low-bandwidth limitations of acoustic channels. This work makes use of a novel forward-scan sonar image coding scheme, where 1) object highlights and shadow edges (treated as foreground) are segmented from the less informative background, maintaining high details for encoding; 2) background is highly compressed to transmit at very little cost; 3) together, they are decoded at the receiver end for reconstruction. Application to various video sequences shows an average compression ratio of 100, for raw video data at 512×96 resolution transmitted at 10 frame per second.

AB - The traditional navigation cameras are being replaced by 2-D forward-scan sonar video devices, when untethered submersible robots operate in underwater environments with poor visibility. A typical FS sonar image comprises of object highlight and cast shadow regions, as well as large relatively uniform background areas, generally corrupted with high level of speckle noise. While both are important in image analysis for object and scene interpretation, highlight and shadow regions encode valuable information for inferring 3-D shape. For some tasks, real-time man-machine interaction and cooperation can significantly enhance the robot performance. The transmission of live video from the robotic platform to a remote surface station requires high video compression ratios to meet the current low-bandwidth limitations of acoustic channels. This work makes use of a novel forward-scan sonar image coding scheme, where 1) object highlights and shadow edges (treated as foreground) are segmented from the less informative background, maintaining high details for encoding; 2) background is highly compressed to transmit at very little cost; 3) together, they are decoded at the receiver end for reconstruction. Application to various video sequences shows an average compression ratio of 100, for raw video data at 512×96 resolution transmitted at 10 frame per second.

UR - http://www.scopus.com/inward/record.url?scp=85061802402&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061802402&partnerID=8YFLogxK

U2 - 10.1109/OCEANS.2018.8604666

DO - 10.1109/OCEANS.2018.8604666

M3 - Conference contribution

T3 - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

BT - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -