The Open UniversitySkip to content
 

Image-Dependent Spatial Shape-Error Concealment

Sohel, Ferdous; Karmakar, Gour and Dooley, Laurence S. (2008). Image-Dependent Spatial Shape-Error Concealment. In: Proceedings of the 9th International Conference on Signal Processing (ICSP'08), 26-29 Oct 2008, Beijing, China.

Full text available as:
[img]
Preview
PDF (Not Set) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (361Kb)
URL: http://icsp08.bjtu.edu.cn/
Google Scholar: Look up in Google Scholar

Abstract

Existing spatial shape-error concealment techniques are broadly based upon either parametric curves that exploit geometric information concerning a shape's contour or object shape statistics using a combination of Markov random fields and maximum a posteriori estimation. Both categories are to some extent, able to mask errors caused by information loss, provided the shape is considered independently of the image/video. They palpably however, do not afford the best solution in applications where shape is used as metadata to describe image and video content. This paper presents a novel image-dependent spatial shape-error concealment (ISEC) algorithm that uses both image and shape information by employing the established rubber-band contour detecting function, with the novel enhancement of automatically determining the optimal width of the band to achieve superior error concealment. Experimental results corroborate both qualitatively and numerically, the enhanced performance of the new ISEC strategy compared with established techniques.

Item Type: Conference Item
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 11063
Depositing User: Laurence Dooley
Date Deposited: 27 Nov 2008 06:20
Last Modified: 24 Feb 2016 21:15
URI: http://oro.open.ac.uk/id/eprint/11063
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk