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Redundancy Removal in Video frames using Luminance Masking

by Snehal A. Patil, Sonal K. Jagtap
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 141 - Number 11
Year of Publication: 2016
Authors: Snehal A. Patil, Sonal K. Jagtap
10.5120/ijca2016909873

Snehal A. Patil, Sonal K. Jagtap . Redundancy Removal in Video frames using Luminance Masking. International Journal of Computer Applications. 141, 11 ( May 2016), 35-39. DOI=10.5120/ijca2016909873

@article{ 10.5120/ijca2016909873,
author = { Snehal A. Patil, Sonal K. Jagtap },
title = { Redundancy Removal in Video frames using Luminance Masking },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 141 },
number = { 11 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume141/number11/24832-2016909873/ },
doi = { 10.5120/ijca2016909873 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:18.712453+05:30
%A Snehal A. Patil
%A Sonal K. Jagtap
%T Redundancy Removal in Video frames using Luminance Masking
%J International Journal of Computer Applications
%@ 0975-8887
%V 141
%N 11
%P 35-39
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Digital video compression techniques have a crucial contribution in the world of telecommunication and multimedia sector where bandwidth is a valued constraint. A large amount of multimedia data has to be stored in a limited storage space. Hence, video compression techniques mainly focus on reducing the volume of information required for picture sequences/streaming pictures without losing much of its quality. Thus, in order to provide an competent compression method for multimedia data, Luminance Masking technique was proposed. In this context, an Intensity Dependant Spatial Quantization (IDSQ) perceptual means is proposed which attempts the intensity masking of the human visual system and perceptually adjusts quantization. IDSQ allows for adaptation to the video characteristics and its design meets low complication implementation requirements The proposed method has been incorporated into the HEVC reference model for the HEVC Range Extensions and its performance was judged by measuring the bit rate reduction against the HEVC Range Extensions.

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Index Terms

Computer Science
Information Sciences

Keywords

HDR HEVC Intensity Dependant Spatial Quantization (IDSQ) Luminance Masking.

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