A novel Image Quality Index for Image Quality Assessment

Sheikh Md. Rabiul Islam, Kim LE, Xu HUANG

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)

Abstract

Image quality assessment (IQA) is provided as computational models to measure the quality of images in perceptually consistent manner. In this paper, a novel image quality index with highlighting shape of histogram of the image targeted is introduced to assess image qualities. The index will be used in place of existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about the distortion between an original image and a distorted image in comparisons with UIQI. The proposed index is designed based on modelling image distortion combinations of four major factors: loss of correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate and applicable in various image processing applications. Experimental results show that the proposed image quality index plays a significantly role in the quality evaluation on the open source “Wireless Imaging Quality (WIQ) database”.
Original languageEnglish
Title of host publicationInternational Conference on Neural Information Processing (ICONIP 2013)
Subtitle of host publicationLecture Notes in Computer Science
EditorsMinho Lee, Akira Hirose, Zeng Guang Hou, Rhee Man Kil
Place of PublicationKorea
PublisherSpringer
Pages549-556
Number of pages8
Volume8228
ISBN (Electronic)9783642420511
ISBN (Print)9783642420504
DOIs
Publication statusPublished - 2013
Event20th International Conference on Neural Information Processing (ICONIP 2013) - Daegu, Daegu, Korea, Republic of
Duration: 3 Nov 20137 Nov 2013

Conference

Conference20th International Conference on Neural Information Processing (ICONIP 2013)
Abbreviated titleICONIP 2013
CountryKorea, Republic of
CityDaegu
Period3/11/137/11/13

Fingerprint

Image quality
Luminance
Image processing
Imaging techniques

Cite this

Islam, S. M. R., LE, K., & HUANG, X. (2013). A novel Image Quality Index for Image Quality Assessment. In M. Lee, A. Hirose, Z. G. Hou, & R. M. Kil (Eds.), International Conference on Neural Information Processing (ICONIP 2013): Lecture Notes in Computer Science (Vol. 8228, pp. 549-556). Korea: Springer. https://doi.org/10.1007/978-3-642-42051-1_68
Islam, Sheikh Md. Rabiul ; LE, Kim ; HUANG, Xu. / A novel Image Quality Index for Image Quality Assessment. International Conference on Neural Information Processing (ICONIP 2013): Lecture Notes in Computer Science. editor / Minho Lee ; Akira Hirose ; Zeng Guang Hou ; Rhee Man Kil. Vol. 8228 Korea : Springer, 2013. pp. 549-556
@inproceedings{f67bedda42d74c3dabfb99bd6bc4dd20,
title = "A novel Image Quality Index for Image Quality Assessment",
abstract = "Image quality assessment (IQA) is provided as computational models to measure the quality of images in perceptually consistent manner. In this paper, a novel image quality index with highlighting shape of histogram of the image targeted is introduced to assess image qualities. The index will be used in place of existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about the distortion between an original image and a distorted image in comparisons with UIQI. The proposed index is designed based on modelling image distortion combinations of four major factors: loss of correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate and applicable in various image processing applications. Experimental results show that the proposed image quality index plays a significantly role in the quality evaluation on the open source “Wireless Imaging Quality (WIQ) database”.",
keywords = "Image, Quality, Assessment",
author = "Islam, {Sheikh Md. Rabiul} and Kim LE and Xu HUANG",
year = "2013",
doi = "10.1007/978-3-642-42051-1_68",
language = "English",
isbn = "9783642420504",
volume = "8228",
pages = "549--556",
editor = "Minho Lee and Akira Hirose and Hou, {Zeng Guang} and Kil, {Rhee Man}",
booktitle = "International Conference on Neural Information Processing (ICONIP 2013)",
publisher = "Springer",
address = "Netherlands",

}

Islam, SMR, LE, K & HUANG, X 2013, A novel Image Quality Index for Image Quality Assessment. in M Lee, A Hirose, ZG Hou & RM Kil (eds), International Conference on Neural Information Processing (ICONIP 2013): Lecture Notes in Computer Science. vol. 8228, Springer, Korea, pp. 549-556, 20th International Conference on Neural Information Processing (ICONIP 2013), Daegu, Korea, Republic of, 3/11/13. https://doi.org/10.1007/978-3-642-42051-1_68

A novel Image Quality Index for Image Quality Assessment. / Islam, Sheikh Md. Rabiul; LE, Kim; HUANG, Xu.

International Conference on Neural Information Processing (ICONIP 2013): Lecture Notes in Computer Science. ed. / Minho Lee; Akira Hirose; Zeng Guang Hou; Rhee Man Kil. Vol. 8228 Korea : Springer, 2013. p. 549-556.

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - A novel Image Quality Index for Image Quality Assessment

AU - Islam, Sheikh Md. Rabiul

AU - LE, Kim

AU - HUANG, Xu

PY - 2013

Y1 - 2013

N2 - Image quality assessment (IQA) is provided as computational models to measure the quality of images in perceptually consistent manner. In this paper, a novel image quality index with highlighting shape of histogram of the image targeted is introduced to assess image qualities. The index will be used in place of existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about the distortion between an original image and a distorted image in comparisons with UIQI. The proposed index is designed based on modelling image distortion combinations of four major factors: loss of correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate and applicable in various image processing applications. Experimental results show that the proposed image quality index plays a significantly role in the quality evaluation on the open source “Wireless Imaging Quality (WIQ) database”.

AB - Image quality assessment (IQA) is provided as computational models to measure the quality of images in perceptually consistent manner. In this paper, a novel image quality index with highlighting shape of histogram of the image targeted is introduced to assess image qualities. The index will be used in place of existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about the distortion between an original image and a distorted image in comparisons with UIQI. The proposed index is designed based on modelling image distortion combinations of four major factors: loss of correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate and applicable in various image processing applications. Experimental results show that the proposed image quality index plays a significantly role in the quality evaluation on the open source “Wireless Imaging Quality (WIQ) database”.

KW - Image

KW - Quality

KW - Assessment

UR - https://link.springer.com/chapter/10.1007/978-3-642-42051-1_68

U2 - 10.1007/978-3-642-42051-1_68

DO - 10.1007/978-3-642-42051-1_68

M3 - Conference contribution

SN - 9783642420504

VL - 8228

SP - 549

EP - 556

BT - International Conference on Neural Information Processing (ICONIP 2013)

A2 - Lee, Minho

A2 - Hirose, Akira

A2 - Hou, Zeng Guang

A2 - Kil, Rhee Man

PB - Springer

CY - Korea

ER -

Islam SMR, LE K, HUANG X. A novel Image Quality Index for Image Quality Assessment. In Lee M, Hirose A, Hou ZG, Kil RM, editors, International Conference on Neural Information Processing (ICONIP 2013): Lecture Notes in Computer Science. Vol. 8228. Korea: Springer. 2013. p. 549-556 https://doi.org/10.1007/978-3-642-42051-1_68