TY - GEN
T1 - On tree-structured Vector quantization over noisy channels
AU - Phamdo, Nam
AU - Farvardin, Nariman
N1 - Publisher Copyright:
© 1991 Institute of Electrical and Electronics Engineers Inc. All rights reserved.
PY - 1991
Y1 - 1991
N2 - Vector quantization (VQ) has been known as an efficient method for data compression [1]. However, a drawback that limits the applicability of VQ is the large encoding complexity associated with the codebook search. Among various techniques used for VQ complexity reduction, tree-structured VQ (TSVQ) [2] has received special attention. Various TSVQ-based schemes have been used successfully in speech and image coding applications (e.g., [3]-[5]). The attractiveness of TSVQ resides in its structured codebook which, in turn, leads to a simple encoding procedure. The penalty paid for using the structured codebook is a modest decrease in performance (higher average distortion for the same bit rate) and a higher memory requirement. To date, there has been little research done on the performance of TSVQ when the data is to be transmitted over a noisy channel. Since in most practical situations, some sort of channel error occurs, the natural questions to ask are: (i) How do TSVQs perform in the presence of channel noise? and (ii) What can be done to improve this performance? This paper will attempt to answer these two questions.
AB - Vector quantization (VQ) has been known as an efficient method for data compression [1]. However, a drawback that limits the applicability of VQ is the large encoding complexity associated with the codebook search. Among various techniques used for VQ complexity reduction, tree-structured VQ (TSVQ) [2] has received special attention. Various TSVQ-based schemes have been used successfully in speech and image coding applications (e.g., [3]-[5]). The attractiveness of TSVQ resides in its structured codebook which, in turn, leads to a simple encoding procedure. The penalty paid for using the structured codebook is a modest decrease in performance (higher average distortion for the same bit rate) and a higher memory requirement. To date, there has been little research done on the performance of TSVQ when the data is to be transmitted over a noisy channel. Since in most practical situations, some sort of channel error occurs, the natural questions to ask are: (i) How do TSVQs perform in the presence of channel noise? and (ii) What can be done to improve this performance? This paper will attempt to answer these two questions.
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U2 - 10.1109/ISIT.1991.695304
DO - 10.1109/ISIT.1991.695304
M3 - Conference contribution
AN - SCOPUS:85067431116
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 248
BT - Proceedings - 1991 IEEE International Symposium on Information Theory, ISIT 1991
T2 - 1991 IEEE International Symposium on Information Theory, ISIT 1991
Y2 - 24 June 1991 through 28 June 1991
ER -