A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain
This article presents a novel full-reference (FR) image quality assessment (QA) algorithm by depicting the sub-band characteristics in the wavelet domain. The proposed image quality assessment method is based on energy estimation in the wavelet-transformed image. Image QA is achieved by applying a m...
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doaj-1b3f6e3174904b1e906824f70032da3f2021-09-06T19:40:35ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2013-06-0122215517710.1515/jisys-2012-0026A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet DomainHanumantharaju M.C.0Ravishankar M.1Rameshbabu D.R.2Aradhya V.N. Manjunath3Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Bangalore, IndiaDepartment of Information Science and Engineering, Dayananda Sagar College of Engineering, Bangalore, IndiaDepartment of Computer Science and Engineering, Dayananda Sagar College of Engineering, Bangalore, IndiaDepartment of MCA (Master of Computer Applications), Sri Jayachamarajendra College of Engineering, Mysore, IndiaThis article presents a novel full-reference (FR) image quality assessment (QA) algorithm by depicting the sub-band characteristics in the wavelet domain. The proposed image quality assessment method is based on energy estimation in the wavelet-transformed image. Image QA is achieved by applying a multilevel wavelet decomposition on both the original and the enhanced image. Next, the wavelet energy (WE) and vector are computed to obtain the percentage of the energy that corresponds to the approximation and the details, respectively. Further, the approximate and detailed energy levels of both the original and the enhanced images are compared to formulate an image quality assessment. Numerous experiments are conducted on a dozen of image enhancement algorithms. The results presented show that the image with poor contrast in the foreground than the background has continuous regular coefficient values. The probability density function for such an image has a relatively lower WE and skewness compared with the background. The proposed scheme not only evaluates the global information of an image but also estimates the fine, detailed changes in an enhanced image. Thus, the proposed metric serves as an objective and effective FR criterion for color image QA. The experimental results presented confirm that the proposed WE metric is an efficient and useful metric for evaluating the quality of the color image enhancement.https://doi.org/10.1515/jisys-2012-0026image enhancementquality assessmentwavelet domainwavelet energy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hanumantharaju M.C. Ravishankar M. Rameshbabu D.R. Aradhya V.N. Manjunath |
spellingShingle |
Hanumantharaju M.C. Ravishankar M. Rameshbabu D.R. Aradhya V.N. Manjunath A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain Journal of Intelligent Systems image enhancement quality assessment wavelet domain wavelet energy |
author_facet |
Hanumantharaju M.C. Ravishankar M. Rameshbabu D.R. Aradhya V.N. Manjunath |
author_sort |
Hanumantharaju M.C. |
title |
A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain |
title_short |
A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain |
title_full |
A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain |
title_fullStr |
A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain |
title_full_unstemmed |
A Novel Full-Reference Color Image Quality Assessment Based on Energy Computation in the Wavelet Domain |
title_sort |
novel full-reference color image quality assessment based on energy computation in the wavelet domain |
publisher |
De Gruyter |
series |
Journal of Intelligent Systems |
issn |
0334-1860 2191-026X |
publishDate |
2013-06-01 |
description |
This article presents a novel full-reference (FR) image quality assessment (QA) algorithm by depicting the sub-band characteristics in the wavelet domain. The proposed image quality assessment method is based on energy estimation in the wavelet-transformed image. Image QA is achieved by applying a multilevel wavelet decomposition on both the original and the enhanced image. Next, the wavelet energy (WE) and vector are computed to obtain the percentage of the energy that corresponds to the approximation and the details, respectively. Further, the approximate and detailed energy levels of both the original and the enhanced images are compared to formulate an image quality assessment. Numerous experiments are conducted on a dozen of image enhancement algorithms. The results presented show that the image with poor contrast in the foreground than the background has continuous regular coefficient values. The probability density function for such an image has a relatively lower WE and skewness compared with the background. The proposed scheme not only evaluates the global information of an image but also estimates the fine, detailed changes in an enhanced image. Thus, the proposed metric serves as an objective and effective FR criterion for color image QA. The experimental results presented confirm that the proposed WE metric is an efficient and useful metric for evaluating the quality of the color image enhancement. |
topic |
image enhancement quality assessment wavelet domain wavelet energy |
url |
https://doi.org/10.1515/jisys-2012-0026 |
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