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Distributed Video Coding using Local Rank Transform

Authors:

Kallol Mallick,

Jayanta MukherjeeAuthors Info & Claims

ICVGIP '14: Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing

Article No.: 18, Pages 1 - 8

https://doi.org/10.1145/2683483.2683501

Published: 14 December 2014 Publication History

Abstract

In today's world, with advanced technology and easily available portable gadgets as enabler, video has become an important medium of communication. While, the standard H.264/AVC has produced extremely good results, it has not been suitable for this application domain as it is computationally intensive and unsuitable for low-power resources. In distributed video coding (DVC), an encoder requires less computation than the decoder, which usually runs at sites of higher computational resources. Our approach is to find out a novel approach in DVC, to reduce encoder complexity, using local rank transform (LRT). LRT relies on the relative ordering of local intensity values for application on visual correspondence problem. Use of LRT in DVC, to the best of our knowledge, has not been reported in literature before. First, we have developed techniques for image reconstruction using LRT and then design a DVC codec using it. We show analytically and by experimental results, that, in power-rate-distortion model, LRT encoder outperforms standard encoder (LDPCA in Stanford architecture) specially in low bit rate condition.

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Cited By

Kamble RAujih BKokare MMeriaudeau F(2018)Detection of Bright and Dark Lesions from Color Fundus Images Using Delta-Rank Transform2018 International Conference on Intelligent and Advanced System (ICIAS)10.1109/ICIAS.2018.8540641(1-6)Online publication date: Aug-2018
https://doi.org/10.1109/ICIAS.2018.8540641
Kamble RKokare M(2017)Detection of microaneurysm using local rank transform in color fundus images2017 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2017.8297122(4442-4446)Online publication date: Sep-2017
https://doi.org/10.1109/ICIP.2017.8297122
Bhagath PMukherjee JMukopadhayay SBatra DBrown MNatarajan V(2016)Low complexity encoder for feedback-channel-free distributed video coding using deep convolutional neural networks at the decoderProceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3009977.3009986(1-7)Online publication date: 18-Dec-2016
https://dl.acm.org/doi/10.1145/3009977.3009986

Index Terms

Distributed Video Coding using Local Rank Transform
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image compression

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Published In

cover image ACM Other conferences

ICVGIP '14: Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing

December 2014

692 pages

ISBN:9781450330619

DOI:10.1145/2683483

General Chairs:
A. G. Ramakrishnan
IISc, Bangalore
,
Jitendra Malik
University California, Berkeley
,
Program Chairs:
Alex Efros
UC-Berkeley
,
C. V. Jawahar
IIIT Hyderabad
,
Manik Varma
Microsoft Research

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 December 2014

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ICVGIP '14

ICVGIP '14: Indian Conference on Computer Vision Graphics and Image Processing

December 14 - 18, 2014

Bangalore, India

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Cited By

Kamble RAujih BKokare MMeriaudeau F(2018)Detection of Bright and Dark Lesions from Color Fundus Images Using Delta-Rank Transform2018 International Conference on Intelligent and Advanced System (ICIAS)10.1109/ICIAS.2018.8540641(1-6)Online publication date: Aug-2018
https://doi.org/10.1109/ICIAS.2018.8540641
Kamble RKokare M(2017)Detection of microaneurysm using local rank transform in color fundus images2017 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2017.8297122(4442-4446)Online publication date: Sep-2017
https://doi.org/10.1109/ICIP.2017.8297122
Bhagath PMukherjee JMukopadhayay SBatra DBrown MNatarajan V(2016)Low complexity encoder for feedback-channel-free distributed video coding using deep convolutional neural networks at the decoderProceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3009977.3009986(1-7)Online publication date: 18-Dec-2016
https://dl.acm.org/doi/10.1145/3009977.3009986

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