Analysis of global spatial statistics features in existing contrast image quality assessment algorithm

Ismail Taha Ahmed, Chen Soong Der, Norziana Jamil, Baraa Tareq Hammad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most of existing image quality assessment algorithms (IQAs) have been developed during the past decade. However, most of them are designed for images distorted by compression, noise and blurring. There are very few IQAs designed specifically for CDI, e.g. Contrast distortion may be caused by poor lighting condition and poor-quality image acquisition device. No Reference-Image Quality Assessment (NR-IQA) for Contrast-Distorted Images (NR-IQA-CDI) is one of these few IQAs. The five features used in NR-IQA-CDI are the global spatial statistics of an image including the mean, standard deviation, entropy, kurtosis and skewness. Unfortunately, the performance of NR-IQA-CDI are not encouraging in two of the three test image databases, TID2013 and CSIQ, where the Pearson Linear Correlation Coefficients are only around 0.57 and 0.76, respectively. Therefore, this paper presents the reason which led to poor results in existing NR-IQA-CDI. This paper also can address the problem of existing NR-IQA-CDI which the weakness of the global features in assessing images with uneven contrast.

Original languageEnglish
Title of host publication2019 7th International Conference on Information and Communication Technology, ICoICT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680520
DOIs
Publication statusPublished - Jul 2019
Event7th International Conference on Information and Communication Technology, ICoICT 2019 - Kuala Lumpur, Malaysia
Duration: 24 Jul 201926 Jul 2019

Publication series

Name2019 7th International Conference on Information and Communication Technology, ICoICT 2019

Conference

Conference7th International Conference on Information and Communication Technology, ICoICT 2019
CountryMalaysia
CityKuala Lumpur
Period24/07/1926/07/19

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Hardware and Architecture

Cite this

Ahmed, I. T., Der, C. S., Jamil, N., & Hammad, B. T. (2019). Analysis of global spatial statistics features in existing contrast image quality assessment algorithm. In 2019 7th International Conference on Information and Communication Technology, ICoICT 2019 [8835319] (2019 7th International Conference on Information and Communication Technology, ICoICT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICoICT.2019.8835319