Data Compression Conference (DCC'05) Quantization of Multiple Sources Using Integer Bit Allocation Snowbird, Utah March 29-March 31 ISBN: 0-7695-2309-9
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DCC.2005.76
Asymptotically optimal bit allocation among a set of quantizers for a finite collection of sources was determined in 1963 by Huang and Schultheiss. Their solution, however, gives a real-valued bit allocation, whereas in practice, integer-valued bit allocations are needed. We compare the performance of the Huang-Schultheiss solution to that of an optimal integer-valued bit allocation. Specifically, we derive upper and lower bounds on the deviation of the mean squared error using optimal integer-valued bit allocation from the mean squared error using optimal real-valued bit allocation. One consequence shown is that optimal integer-valued bit allocations do not necessarily achieve the same performance as that predicted by Huang-Schultheiss, for asymptotically large transmission rates. We also prove that integer bit allocation vectors that minimize the Euclidean distance to the optimal real-valued bit allocation vector are optimal integer bit allocations.
Citation:
Benjamin Farber, Kenneth Zeger, "Quantization of Multiple Sources Using Integer Bit Allocation," dcc, pp.368-377, Data Compression Conference (DCC'05), 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||