The authors introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, stationary sources. The algorithm is set on line without any prior knowledge of the statistics of the sources which it might encounter and asymptotically achieves ideal performance on all sources that it sees. The system consists of an encoder and a decoder. At increasing intervals, the encoder refines its codebook using knowledge about incoming data symbols. This codebook is then described to the decoder in the form of updates on the previous codebook. The accuracy to which the codebook is described increases as the number of symbols seen, and thus the accuracy to which the codebook is known, grows
Rissanen has shown that there exist universal noiseless codes for {Xi} with per-letter rate redundan...
This article examines the problem of compressing a uniformly quantized independent and identically d...
Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression...
We introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, statio...
We consider the problem of adaptive universal quantization. By adaptive quantization we mean quantiz...
Abstract-Rate of convergence results are established for vector quantization. Convergence rates are ...
International audienceThis paper sheds light on universal coding with respect to classes of memoryle...
Vector quantization is known to be an effective compression scheme to achieve a low bit rate so as t...
International audienceThis paper sheds light on universal coding with respect to classes of memoryle...
In this paper, we study the problem of lossless universal source coding for stationary memoryless so...
Rissanen has shown that there exist universal noiseless codes for {Xi} with per-letter rate redundan...
Vector quantization (VQ) has long been a popular technique for data compression due in part to resul...
A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented...
33 pagesInternational audienceThis paper describes universal lossless coding strategies for compress...
Multiresolution source codes are data compression algorithms yielding embedded source descriptions. ...
Rissanen has shown that there exist universal noiseless codes for {Xi} with per-letter rate redundan...
This article examines the problem of compressing a uniformly quantized independent and identically d...
Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression...
We introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, statio...
We consider the problem of adaptive universal quantization. By adaptive quantization we mean quantiz...
Abstract-Rate of convergence results are established for vector quantization. Convergence rates are ...
International audienceThis paper sheds light on universal coding with respect to classes of memoryle...
Vector quantization is known to be an effective compression scheme to achieve a low bit rate so as t...
International audienceThis paper sheds light on universal coding with respect to classes of memoryle...
In this paper, we study the problem of lossless universal source coding for stationary memoryless so...
Rissanen has shown that there exist universal noiseless codes for {Xi} with per-letter rate redundan...
Vector quantization (VQ) has long been a popular technique for data compression due in part to resul...
A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented...
33 pagesInternational audienceThis paper describes universal lossless coding strategies for compress...
Multiresolution source codes are data compression algorithms yielding embedded source descriptions. ...
Rissanen has shown that there exist universal noiseless codes for {Xi} with per-letter rate redundan...
This article examines the problem of compressing a uniformly quantized independent and identically d...
Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression...