This correspondence presents entropy analyses for dithered and undithered quantized sources. Two methods are discussed that reduce the increase in entropy caused by the dither. The first method supplies the dither to the lossless encoding-decoding scheme. It is argued that this increases the complexity of the encoding-decoding scheme. A method to reduce this complexity is proposed. The second method is the usage of a dead-zone quantizer. A procedure for determining the optimal dead-zone width in the mean-square sense is give
Abstract—We analyze the behaviour of the mean squared error (MSE) achievable by oversampled, uniform...
Abstract—Randomized (dithered) quantization is a method ca-pable of achieving white reconstruction e...
This study is divided into two parts. The first part involves an investigation of near-lossless comp...
This correspondence presents entropy analyses for dithered and undithered quantized sources. Two met...
A theoretical survey of multibit quantization is presented, beginning with the classical model of un...
Assuming the squared error distortion measure, we bound the performance achieved by using scalar ent...
Data compression is the art of using encoding techniques to represent data symbols using less storag...
We consider encoding of a source with a pre-specified second order statistics, but otherwise arbitra...
We introduce a debiasing scheme that solves the more noise than entropy problem which can occur in H...
Dithered quantization and noise shaping is well known in the audio community. The image processing ...
In this paper, we build multiresolution source codes using entropy constrained dithered scalar quant...
Data Compression Due to limitations in data storage and bandwidth, data of all types has often requi...
We introduce a universal quantization scheme based on random coding, and we analyze its performance....
International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and C...
In this paper, we build multi-resolution source codes using entropy con-strained dithered scalar qua...
Abstract—We analyze the behaviour of the mean squared error (MSE) achievable by oversampled, uniform...
Abstract—Randomized (dithered) quantization is a method ca-pable of achieving white reconstruction e...
This study is divided into two parts. The first part involves an investigation of near-lossless comp...
This correspondence presents entropy analyses for dithered and undithered quantized sources. Two met...
A theoretical survey of multibit quantization is presented, beginning with the classical model of un...
Assuming the squared error distortion measure, we bound the performance achieved by using scalar ent...
Data compression is the art of using encoding techniques to represent data symbols using less storag...
We consider encoding of a source with a pre-specified second order statistics, but otherwise arbitra...
We introduce a debiasing scheme that solves the more noise than entropy problem which can occur in H...
Dithered quantization and noise shaping is well known in the audio community. The image processing ...
In this paper, we build multiresolution source codes using entropy constrained dithered scalar quant...
Data Compression Due to limitations in data storage and bandwidth, data of all types has often requi...
We introduce a universal quantization scheme based on random coding, and we analyze its performance....
International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and C...
In this paper, we build multi-resolution source codes using entropy con-strained dithered scalar qua...
Abstract—We analyze the behaviour of the mean squared error (MSE) achievable by oversampled, uniform...
Abstract—Randomized (dithered) quantization is a method ca-pable of achieving white reconstruction e...
This study is divided into two parts. The first part involves an investigation of near-lossless comp...