By Topic

Multidescription video streaming with optimized reconstruction-based DCT and neural-network compensations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xiao Su ; Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA ; Web, W.

Packet and compression losses are two sources of quality losses when streaming compressed video over unreliable IP networks, such as the Internet. In this paper, we propose two new approaches for concealing such losses. First, we present a joint sender-receiver approach for designing transforms in multidescription coding (MDC). In the receiver, we use a simple interpolation-based reconstruction algorithm, as sophisticated concealment techniques cannot be employed in real time. In the sender we design an optimized reconstruction-based discrete cosine transform (ORB-DCT) with an objective of minimizing the mean squared error, assuming that some of the descriptions are lost and that the missing information is reconstructed by simple averaging at the destination. Second, we propose artificial neural network to compensate for compression losses introduced in MDC. Experimental results show that our proposed algorithms perform well in real internet tests

Published in:

Multimedia, IEEE Transactions on  (Volume:3 ,  Issue: 1 )