Abstract
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.
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 language | English |
|---|---|
| Title of host publication | Proceedings of British Machine Vision Conference (BMVC) 2008 |
| Editors | Mark Everingham, Chris Needham, Roberto Fraile |
| Publisher | BMVA |
| Pages | 373-382 |
| Number of pages | 10 |
| ISBN (Electronic) | 978 1 901725 37 7 |
| ISBN (Print) | 978 1 901725 36 0 |
| Publication status | Published - Sep 2008 |
| Event | British Machine Vision Conference 2008 - Leeds, United Kingdom Duration: 1 Sep 2008 → 4 Sep 2008 |
Conference
| Conference | British Machine Vision Conference 2008 |
|---|---|
| Country/Territory | United Kingdom |
| City | Leeds |
| Period | 1/09/08 → 4/09/08 |