Open AccessAnalysis of wavelet-based full reference image quality assessment algorithm
Author(s) -
Faizah Mokhtar,
Ruzelita Ngadiran,
Taha Basheer,
Amir Nazren Abdul Rahim
Publication year - 2019
Publication title -
bulletin of electrical engineering and informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 12
ISSN - 2302-9285
DOI - 10.11591/eei.v8i2.1404
Subject(s) - wavelet , image quality , distortion (music) , computer science , image (mathematics) , artificial intelligence , image processing , algorithm , pattern recognition (psychology) , quality (philosophy) , data mining , amplifier , computer network , philosophy , bandwidth (computing) , epistemology
Measurement of Image Quality plays an important role in numerous image processing applications such as forensic science, image enhancement, medical imaging, etc. In recent years, there is a growing interest among researchers in creating objective Image Quality Assessment (IQA) algorithms that can correlate well with perceived quality. A significant progress has been made for full reference (FR) IQA problem in the past decade. In this paper, we are comparing 5 selected FR IQA algorithms on TID2008 image datasets. The performance and evaluation results are shown in graphs and tables. The results of quantitative assessment showed wavelet-based IQA algorithm outperformed over the non-wavelet based IQA method except for WASH algorithm which the prediction value only outperformed for certain distortion types since it takes into account the essential structural data content of the image.