Junyong You
ABSTRACT
Most existing quality metrics do not take the human attention analysis into account. Attention to particular objects or regions is an important attribute of human vision and perception system in measuring perceived image and video qualities. This paper presents an approach for extracting visual attention regions based on a combination of a bottom-up saliency model and semantic image analysis. The use of PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural SIMilarity) in extracted attention regions is analyzed for image/video quality assessment, and a novel quality metric is proposed which can exploit the attributes of visual attention information adequately. The experimental results with respect to the subjective measurement demonstrate that the proposed metric outperforms the current methods.
- Winkler, S. 2005. Digital video quality: vision models and metrics, John Wiley&Sons Press.Google Scholar
- Pinson, M. and Wolf S. 2004. A new standardized method for objectively measuring video quality. IEEE Trans. Broadcasting, 50 (Sep. 2004), 312--322.Google ScholarCross Ref
- Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P. 2004. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Processing, 13 (Apr. 2004), 600--612. Google ScholarDigital Library
- Itti L. and Koch C. 2001. Computational modeling of visual attention, Nat. Rev. Neurosci., 2 (Mar. 2001), 194--203.Google ScholarCross Ref
- Lu Z., Lin W., Yang X., et al. 2005. Modeling visual attention's modulatory aftereffects on visual sensitivity and quality evaluation. IEEE Trans. Image Processing, 14 (Nov. 2005), 1928--1942.Google ScholarDigital Library
- Feng X., Liu T., Yang D., and Wang Y. 2008. Saliency based objective quality assessment of decoded video affected by packet losses. In Proceedings of IEEE Int. Conf. Image Processing (California, USA, Oct. 12--15, 2008), 2560--2563.Google Scholar
- SaliencyToolbox 2.1, http://www.saliencytoolbox.net.Google Scholar
- Sheikh H. R., Wang, Z., Cormack L., and Bovik A. C. LIVE Image Quality Assessment Database. http://live.ece.utexas.edu/research/quality.Google Scholar
- VQEG Sequence, ftp://ftp.crc.ca/crc/vqeg/TestSequences/.Google Scholar
- Pinson, M. and Wolf, S. 2003. An Objective Method for Combining Multiple Subjective Data Sets. In Proc. SPIE Video Communication and Image Processing Conf. (Lugano, Switzerland, Jul. 2003), 583--592.Google Scholar
Index Terms
- Perceptual quality assessment based on visual attention analysis
Recommendations
Stereoscopic Images Quality Assessment with Visual Attention
ISCID '13: Proceedings of the 2013 Sixth International Symposium on Computational Intelligence and Design - Volume 01Stereoscopic images have been widely studied in recent years from a technical point of view, but the related quality assessment does not follow this enthusiasm. An objective quality assessment with visual attention for stereoscopic images is proposed, ...
Stereoscopic Images Quality Assessment with Visual Attention
ICEICE '12: Proceedings of the 2012 Second International Conference on Electric Information and Control Engineering - Volume 01Stereoscopic images have been widely studied in recent years from a technical point of view, but the related quality assessment does not follow this enthusiasm. An objective quality assessment with visual attention for stereoscopic images is proposed, ...
Image quality assessment metrics combining structural similarity and image fidelity with visual attention
Image quality assessment has a great importance in several image processing applications. Recently, various objective image quality metrics have been proposed in order to predict human visual perception. In this paper, novel image quality metrics, S-...
Comments