Seafloor image compression using hybrid wavelets and directional filter banks

Y. Zhang; Q. Z. Li; Shahriar Negahdaripour

doi:10.1109/OCEANS-Genova.2015.7271251

Seafloor image compression using hybrid wavelets and directional filter banks

Y. Zhang, Q. Z. Li, Shahriar Negahdaripour

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

We present an efficient compression method based on the hybrid wavelets and directional filter banks (HWD), to achieve high compression efficiency while keeping visually pleasing reconstruction quality for underwater images. According to the characteristics of underwater images and the human vision system (HVS), an improved just noticeable distortion (JND) model is initially employed to adaptively remove the visual redundancy of underwater images in the HWD domain. The low-frequency coefficients are then quantized in the fixed length and encoded losslessly. The high-frequency coefficients are quantized by variable precision and fixed length method, and are coded by the difference reduction algorithm based on HWD trees. The experimental results show that the proposed compression algorithm provides both high coding efficiency and satisfactory reconstruction quality, which is highly desired for the transmission of underwater images at very low-bit rates.

Original language	English (US)
Title of host publication	MTS/IEEE OCEANS 2015 - Genova: Discovering Sustainable Ocean Energy for a New World
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781479987368
DOIs	https://doi.org/10.1109/OCEANS-Genova.2015.7271251
State	Published - Sep 17 2015
Event	MTS/IEEE OCEANS 2015 - Genova - Genova, Italy Duration: May 18 2015 → May 21 2015

Other

Other	MTS/IEEE OCEANS 2015 - Genova
Country	Italy
City	Genova
Period	5/18/15 → 5/21/15

Keywords

HWD transform
image compression
just noticeable distortion
low-bit-rate coding
underwater imaging

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Oceanography

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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10.1109/OCEANS-Genova.2015.7271251

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Seafloor image compression using hybrid wavelets and directional filter banks. / Zhang, Y.; Li, Q. Z.; Negahdaripour, Shahriar.

MTS/IEEE OCEANS 2015 - Genova: Discovering Sustainable Ocean Energy for a New World. Institute of Electrical and Electronics Engineers Inc., 2015. 7271251.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, Y, Li, QZ & Negahdaripour, S 2015, Seafloor image compression using hybrid wavelets and directional filter banks. in MTS/IEEE OCEANS 2015 - Genova: Discovering Sustainable Ocean Energy for a New World., 7271251, Institute of Electrical and Electronics Engineers Inc., MTS/IEEE OCEANS 2015 - Genova, Genova, Italy, 5/18/15. https://doi.org/10.1109/OCEANS-Genova.2015.7271251

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abstract = "We present an efficient compression method based on the hybrid wavelets and directional filter banks (HWD), to achieve high compression efficiency while keeping visually pleasing reconstruction quality for underwater images. According to the characteristics of underwater images and the human vision system (HVS), an improved just noticeable distortion (JND) model is initially employed to adaptively remove the visual redundancy of underwater images in the HWD domain. The low-frequency coefficients are then quantized in the fixed length and encoded losslessly. The high-frequency coefficients are quantized by variable precision and fixed length method, and are coded by the difference reduction algorithm based on HWD trees. The experimental results show that the proposed compression algorithm provides both high coding efficiency and satisfactory reconstruction quality, which is highly desired for the transmission of underwater images at very low-bit rates.",

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AB - We present an efficient compression method based on the hybrid wavelets and directional filter banks (HWD), to achieve high compression efficiency while keeping visually pleasing reconstruction quality for underwater images. According to the characteristics of underwater images and the human vision system (HVS), an improved just noticeable distortion (JND) model is initially employed to adaptively remove the visual redundancy of underwater images in the HWD domain. The low-frequency coefficients are then quantized in the fixed length and encoded losslessly. The high-frequency coefficients are quantized by variable precision and fixed length method, and are coded by the difference reduction algorithm based on HWD trees. The experimental results show that the proposed compression algorithm provides both high coding efficiency and satisfactory reconstruction quality, which is highly desired for the transmission of underwater images at very low-bit rates.

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Seafloor image compression using hybrid wavelets and directional filter banks

Abstract

Other

Keywords

ASJC Scopus subject areas

UN SDGs

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