Eigen-Gap Of Structure Transition Matrix: A New Criterion For Image Quality Assessment
Keywords
Eigen-gap; Image Quality Assessment; Structural Clustering; Transition Matrix
Abstract
A new approach to Image Quality Assessment (IQA) is presented. The idea is based on the fact that two images are similar if their structural relationship within their blocks is preserved. To this end, a transition matrix is defined which exploits structural transitions between corresponding blocks of two images. The matrix contains valuable information about differences of two images, which should be transformed to a quality index. Eigen-value analysis over the transition matrix leads to a new distance measure called Eigen-gap. According to simulation results, the Eigen-gap is not only highly correlated to subjective scores but also, its performance is as good as the SSIM, a trustworthy index.
Publication Date
12-30-2015
Publication Title
2015 IEEE Signal Processing and Signal Processing Education Workshop, SP/SPE 2015
Number of Pages
370-375
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/DSP-SPE.2015.7369582
Copyright Status
Unknown
Socpus ID
84963997554 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84963997554
STARS Citation
Joneidi, M.; Rahmani, M.; Golestani, H. B.; and Ghanbari, M., "Eigen-Gap Of Structure Transition Matrix: A New Criterion For Image Quality Assessment" (2015). Scopus Export 2015-2019. 1959.
https://stars.library.ucf.edu/scopus2015/1959