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Image Contrast Enhancement using Learning Vector Quantization

by Priyanka Yadav, Vineet Khanna
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 20
Year of Publication: 2018
Authors: Priyanka Yadav, Vineet Khanna
10.5120/ijca2018917911

Priyanka Yadav, Vineet Khanna . Image Contrast Enhancement using Learning Vector Quantization. International Journal of Computer Applications. 181, 20 ( Oct 2018), 29-35. DOI=10.5120/ijca2018917911

@article{ 10.5120/ijca2018917911,
author = { Priyanka Yadav, Vineet Khanna },
title = { Image Contrast Enhancement using Learning Vector Quantization },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 20 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 29-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number20/30003-2018917911/ },
doi = { 10.5120/ijca2018917911 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:30.669385+05:30
%A Priyanka Yadav
%A Vineet Khanna
%T Image Contrast Enhancement using Learning Vector Quantization
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 20
%P 29-35
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Human is gifted by god with five senses – sight, hearing, touch, smell and taste – which humans use to perceive their environment. Out of these five senses, sight is the most powerful. Image Contrast Enhancement with brightness preserving is a simple, effective and most widely used area among all digital image processing techniques. The goal of brightness preserving and contrast enhancement in general is to provide a more appealing image and clarity of details. These enhancements are intimately related to different attributes of visual sensation. In this paper we propose a method of image enhancement using Learning Vector Quantization for feature enhancement. Result shows a significant performance improvement by applying LVQ. Proposed method results generate better values of Absolute Mean Brightness Error (AMBE) and Peak Signal to Noise Ratio (PSNR) than other Histogram Equalization (HE) method.

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Index Terms

Computer Science
Information Sciences

Keywords

LVQ HE AMBE PSNR

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