We consider the lossy image compression problem and propose a model-residual approach. Polynomial basis images encode the model image and powerful new trellis codes quantize the residual part. A simple bit allocation scheme determines the residual bit rates and a variety of rates are attainable without entropy coding. The trellis structure is also used to form a joint source and channel coding scheme for the residual components. Results are shown for the 0.4-1.6 bits per pixel region. Comparisons are made to several state-of-the-art techniques and show that the proposed scheme is very competitiv
Trellis coded quantization (TCQ) is incorporated into a transform coding structure for encoding mono...
The main focus of research in stereo image coding has been disparity estimation (DE), a technique us...
In this dissertation, adaptive wavelet and transform coding techniques are presented for low bit-rat...
We present a new Trellis Coded Vector Residual Quantizer (TCVRQ) that combines trellis coding and ve...
We present a new Trellis Coded Vector Residual Quantizer (TCVRQ) that combines trellis coding and ve...
We propose a fast trellis-based rate-allocation algorithm for robust transmission of progressively c...
In this paper, we present coding techniques that enable progressive transmission when trellis coded ...
Robust source coding provides both compression and noise mitigation without channel coding. In this ...
Trellis quantization is a finite state machine based method for data compression. It is mainly appli...
International audienceIn this paper, we propose a complete transmission system for still images whic...
Trellis coded quantization has recently evolved as a powerful quantization technique in the world of...
Lossy plus lossless techniques for image compression split an image into a low-bit-rate lossy repres...
This paper presents a new Trellis Coded Vector Residual Quantizer (or TCVRQ) that combines trellis c...
A novel scheme for joint source/channel coding of still images is proposed. By using efficient lappe...
BCJR based source coding of image residuals is explored. From a trellis representation of the residu...
Trellis coded quantization (TCQ) is incorporated into a transform coding structure for encoding mono...
The main focus of research in stereo image coding has been disparity estimation (DE), a technique us...
In this dissertation, adaptive wavelet and transform coding techniques are presented for low bit-rat...
We present a new Trellis Coded Vector Residual Quantizer (TCVRQ) that combines trellis coding and ve...
We present a new Trellis Coded Vector Residual Quantizer (TCVRQ) that combines trellis coding and ve...
We propose a fast trellis-based rate-allocation algorithm for robust transmission of progressively c...
In this paper, we present coding techniques that enable progressive transmission when trellis coded ...
Robust source coding provides both compression and noise mitigation without channel coding. In this ...
Trellis quantization is a finite state machine based method for data compression. It is mainly appli...
International audienceIn this paper, we propose a complete transmission system for still images whic...
Trellis coded quantization has recently evolved as a powerful quantization technique in the world of...
Lossy plus lossless techniques for image compression split an image into a low-bit-rate lossy repres...
This paper presents a new Trellis Coded Vector Residual Quantizer (or TCVRQ) that combines trellis c...
A novel scheme for joint source/channel coding of still images is proposed. By using efficient lappe...
BCJR based source coding of image residuals is explored. From a trellis representation of the residu...
Trellis coded quantization (TCQ) is incorporated into a transform coding structure for encoding mono...
The main focus of research in stereo image coding has been disparity estimation (DE), a technique us...
In this dissertation, adaptive wavelet and transform coding techniques are presented for low bit-rat...