Predictive fusion coding of spatio-temporally correlated sources

This paper considers the problem of predictive fusion coding for storage of multiple spatio-temporally correlated sources so as to enable efficient selective retrieval of data from subsets of sources as designated by future queries. Only statistical information about future queries is available during encoding. While temporal correlations can be exploited by coding over large blocks, the growth in encoding complexity renders this approach impractical and hence the interest in a low complexity predictive coding approach. However, the design of optimal predictive fusion coding systems is considerably complicated by the presence of the prediction loop, and the potentially exponential growth of the query sets. We propose a complexity-constrained predictive fusion coder and derive an iterative algorithm for its design, which is based on the ”Asymptotic Closed Loop” framework and hence, circumvents convergence and stability issues of traditional predictive quantizer design. The propose...

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Sharadh Ramaswamy, Kenneth Rose
• Keywords: Fusion Coding, ICASSP 2008, Predictive Fusion, Predictive Fusion Coder, Signal Processing