EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images

Muhammad Umair Mukati; Søren Forchhammer

doi:10.1109/DCC47342.2020.00012

EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images

Muhammad Umair Mukati, Søren Forchhammer

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Abstract

This paper proposes extensions of CALIC for lossless compression of light field (LF) images. The overall prediction process is improved by exploiting the linear structure of Epipolar Plane Images (EPI) in a slope based prediction scheme. The prediction is improved further by averaging predictions made using horizontal and verticals EPIs. Besides this, the difference in these predictions is included in the error energy function, and the texture context is redefined to improve the overall compression ratio. The results using the proposed method shows significant bitrate-savings in comparison to standard lossless coding schemes and offers significant reduction in computational complexity in comparison to the state-of-the-art compression schemes.

Original language	English
Title of host publication	Proceedings of 2020 Data Compression Conference
Publisher	IEEE
Publication date	2020
Pages	43-52
Article number	167
ISBN (Print)	9781728164571
DOIs	https://doi.org/10.1109/DCC47342.2020.00012
Publication status	Published - 2020
Event	2020 Data Compression Conference - Virtual Conference, Snowbird, United States Duration: 24 Mar 2020 → 27 Mar 2020 https://ieeexplore.ieee.org/xpl/conhome/9102212/proceeding

Conference

Conference	2020 Data Compression Conference
Location	Virtual Conference
Country/Territory	United States
City	Snowbird
Period	24/03/2020 → 27/03/2020
Internet address	https://ieeexplore.ieee.org/xpl/conhome/9102212/proceeding

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@inproceedings{81c1bf352d264e69888bcd2fa97e529a,

title = "EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images",

abstract = "This paper proposes extensions of CALIC for lossless compression of light field (LF) images. The overall prediction process is improved by exploiting the linear structure of Epipolar Plane Images (EPI) in a slope based prediction scheme. The prediction is improved further by averaging predictions made using horizontal and verticals EPIs. Besides this, the difference in these predictions is included in the error energy function, and the texture context is redefined to improve the overall compression ratio. The results using the proposed method shows significant bitrate-savings in comparison to standard lossless coding schemes and offers significant reduction in computational complexity in comparison to the state-of-the-art compression schemes.",

author = "Mukati, {Muhammad Umair} and S{\o}ren Forchhammer",

year = "2020",

doi = "10.1109/DCC47342.2020.00012",

language = "English",

isbn = "9781728164571",

pages = "43--52",

booktitle = "Proceedings of 2020 Data Compression Conference",

publisher = "IEEE",

address = "United States",

note = "2020 Data Compression Conference, DCC 2020 ; Conference date: 24-03-2020 Through 27-03-2020",

url = "https://ieeexplore.ieee.org/xpl/conhome/9102212/proceeding",

}

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T1 - EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images

AU - Mukati, Muhammad Umair

AU - Forchhammer, Søren

PY - 2020

Y1 - 2020

N2 - This paper proposes extensions of CALIC for lossless compression of light field (LF) images. The overall prediction process is improved by exploiting the linear structure of Epipolar Plane Images (EPI) in a slope based prediction scheme. The prediction is improved further by averaging predictions made using horizontal and verticals EPIs. Besides this, the difference in these predictions is included in the error energy function, and the texture context is redefined to improve the overall compression ratio. The results using the proposed method shows significant bitrate-savings in comparison to standard lossless coding schemes and offers significant reduction in computational complexity in comparison to the state-of-the-art compression schemes.

AB - This paper proposes extensions of CALIC for lossless compression of light field (LF) images. The overall prediction process is improved by exploiting the linear structure of Epipolar Plane Images (EPI) in a slope based prediction scheme. The prediction is improved further by averaging predictions made using horizontal and verticals EPIs. Besides this, the difference in these predictions is included in the error energy function, and the texture context is redefined to improve the overall compression ratio. The results using the proposed method shows significant bitrate-savings in comparison to standard lossless coding schemes and offers significant reduction in computational complexity in comparison to the state-of-the-art compression schemes.

U2 - 10.1109/DCC47342.2020.00012

DO - 10.1109/DCC47342.2020.00012

M3 - Article in proceedings

SN - 9781728164571

SP - 43

EP - 52

BT - Proceedings of 2020 Data Compression Conference

PB - IEEE

T2 - 2020 Data Compression Conference

Y2 - 24 March 2020 through 27 March 2020

ER -

EPIC: Context Adaptive Lossless Light Field Compression using Epipolar Plane Images

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