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

5 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

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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