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New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction

Journal of ICT Research and Applications (JICTRA) · Vol. 15 No. 3 (2021) · pp. 239–250

DOI
10.5614/itbj.ict.res.appl.2021.15.3.3
ISSN
2338-5499, 2337-5787
Published
2021-12-28
Publisher
DRI - ITB
Language
eng

Abstract

This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.

Keywords

Collaboration network of the authors

36 authors · 96 co-authorship links · 9 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universiti Teknikal Malaysia Melaka
  • Rabdan Academy
  • Binus University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Norlezah HashimUniversiti Teknikal Malaysia Melaka2
Fakrulradzi IdrisUniversiti Teknikal Malaysia Melaka2
Shamsul Fakhar Abd GaniUniversiti Teknikal Malaysia Melaka2
M. Saad HUniversiti Teknikal Malaysia Melaka2
A. Fauzan KUniversiti Teknikal Malaysia Melaka2
Mustafa Emad HameedUniversiti Teknikal Malaysia Melaka2
Masrullizam Mat IbrahimUniversiti Teknikal Malaysia Melaka2
Siti Asma Che AzizUniversiti Teknikal Malaysia Melaka2
N. RahimUniversiti Teknikal Malaysia Melaka2
Wan Haszerila Wan HassanUniversiti Teknikal Malaysia Melaka2
I. F. A. AzizUniversiti Teknikal Malaysia Melaka2
Mohd Saad HamidUniversiti Teknikal Malaysia Melaka2
Aiman Zakwan JidinUniversiti Teknikal Malaysia Melaka1
Lim Siau LiUniversiti Teknikal Malaysia Melaka1
Siti Suhaila Jaapar SidekUniversiti Teknikal Malaysia Melaka1
M. Aidil A.Universiti Teknikal Malaysia Melaka1
Keshu FenUniversiti Teknikal Malaysia Melaka1
Lee Boon YeeUniversiti Teknikal Malaysia Melaka1
Mothana Lafta AttiahUniversiti Teknikal Malaysia Melaka1
Melvin Gan Yeou WeiUniversiti Teknikal Malaysia Melaka1
Nik Syahrim Nik AnwarUniversiti Teknikal Malaysia Melaka1
Ali Abdul-Jabbar MohammedUniversiti Teknikal Malaysia Melaka1
A. M. DarsonoUniversiti Teknikal Malaysia Melaka1
C. C. TohUniversiti Teknikal Malaysia Melaka1
Nik Mohd Zarifie HashimUniversiti Teknikal Malaysia Melaka1
Jamil Abedalrahim Jamil AlsayaydehUniversiti Teknikal Malaysia Melaka1
Mohd Faizal YusofRabdan Academy1
Mithilanandini S. MagenthiranUniversiti Teknikal Malaysia Melaka1
Izadora Binti MustaffaUniversiti Teknikal Malaysia Melaka1
Safarudin Gazali HerawanBinus University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction</dc:title>
	<dc:creator>Fauzan, Ahmad</dc:creator>
	<dc:creator>Affendi, Rostam</dc:creator>
	<dc:creator>Abd. Manap, Nurulfajar</dc:creator>
	<dc:creator>Saad, Mohd</dc:creator>
	<dc:creator>Nadzrie, Nadzrie</dc:creator>
	<dc:creator>Faisal, Tg. Mohd</dc:creator>
	<dc:subject xml:lang="en-US">adaptive gamma correction</dc:subject>
	<dc:subject xml:lang="en-US">adaptive histogram equalization</dc:subject>
	<dc:subject xml:lang="en-US"> pre-processing</dc:subject>
	<dc:subject xml:lang="en-US">stereo matching algorithm</dc:subject>
	<dc:subject xml:lang="en-US">stereo vision</dc:subject>
	<dc:description xml:lang="en-US">This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2021-12-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/15431</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2021.15.3.3</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 15 No. 3 (2021); 239-250</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2021.15.3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/15431/5560</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Journal of ICT Research and Applications</dc:rights>
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