An image quality metric based on corner, edge and symmetry maps

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

16 Citations (Scopus)


Image quality metrics have been widely used in imaging systems to maintain
and improve the quality of images being processed and transmitted. Due
to the close relationship between image quality perception and human visual
system, the development of image quality metrics (IQMs) has been
contributed to by both psychologists and computer scientists. In this paper,
three novel image quality metrics have been proposed by improving
the well-known image quality metric structure similarity index (SSIM). In
this new approach, images are not compared directly, but their feature maps
are (preprocessing is incorporated to extract the corner, edge and symmetry
maps). The similarity measured (by SSIM) between corner, edge and symmetry
maps of images being compared is used as an indicator of image quality,
and named C SSIM, E SSIM and S SSIM respectively. The experiments
show that all the proposed image quality metrics have a better performance
than SSIM, and E SSIM has the best performance among them.
Original languageEnglish
Title of host publicationProceedings of British Machine Vision Conference (BMVC) 2008
EditorsMark Everingham, Chris Needham, Roberto Fraile
Number of pages10
ISBN (Electronic)978 1 901725 37 7
ISBN (Print)978 1 901725 36 0
Publication statusPublished - Sept 2008
EventBritish Machine Vision Conference 2008 - Leeds, United Kingdom
Duration: 1 Sept 20084 Sept 2008


ConferenceBritish Machine Vision Conference 2008
Country/TerritoryUnited Kingdom


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