Vector quantization and signal compression
Vector quantization and signal compression
Elements of information theory
Elements of information theory
Arithmetic coding for data compression
Communications of the ACM
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Joint Source-Channel Coding for Progressive Transmission of Embedded Source Coders
DCC '99 Proceedings of the Conference on Data Compression
Compression with Side Information Using Turbo Codes
DCC '02 Proceedings of the Data Compression Conference
Joint Source-Channel Coding at the Application Layer
DCC '09 Proceedings of the 2009 Data Compression Conference
Computer Networking: A Top-Down Approach
Computer Networking: A Top-Down Approach
The empirical distribution of good codes
IEEE Transactions on Information Theory
Optimal entropy-constrained scalar quantization of a uniform source
IEEE Transactions on Information Theory
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
The capacity of low-density parity-check codes under message-passing decoding
IEEE Transactions on Information Theory
Hybrid digital-analog (HDA) joint source-channel codes for broadcasting and robust communications
IEEE Transactions on Information Theory
A broadcast approach for a single-user slowly fading MIMO channel
IEEE Transactions on Information Theory
Design methods for irregular repeat-accumulate codes
IEEE Transactions on Information Theory
Universal discrete denoising: known channel
IEEE Transactions on Information Theory
Low-resolution scalar quantization for Gaussian sources and squared error
IEEE Transactions on Information Theory
Raptor codes on binary memoryless symmetric channels
IEEE Transactions on Information Theory
Hybrid Digital–Analog Source–Channel Coding for Bandwidth Compression/Expansion
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Progressive transmission of images over memoryless noisy channels
IEEE Journal on Selected Areas in Communications
Error-resilient coding in JPEG-2000 and MPEG-4
IEEE Journal on Selected Areas in Communications
On the iterative approximation of optimal joint source-channel decoding
IEEE Journal on Selected Areas in Communications
Fast algorithm for distortion-based error protection of embedded image codes
IEEE Transactions on Image Processing
Hi-index | 754.84 |
We present a general scheme for the lossy transmission of a source with arbitrary statistics through a noisy channel under the mean-square error fidelity criterion. Our approach is based on transform coding, scalar quantization of the transform coefficients and linear encoding of the quantization indices. Entropy coding and channel coding are merged into a single linear encoding function, such that the "catastrophic" behavior of conventional entropy coding is avoided and the full power of modern coding techniques and iterative "Belief-Propagation" decoding can be exploited. We show that this approach is asymptotically optimal in the limit of large block length, for arbitrary source statistics and binary-input output-symmetric channel. In the practical regime of finite block length and low decoding complexity, we show, through the explicit construction of codes for the lossy transmission of digital images over a binary symmetric channel, that our approach yields significant improvements with respect to previously proposed channel-optimized quantization schemes and also with respect to the conventional concatenation of state-of-the art image coding with state-of-the art channel coding. Although our constructive example focuses on a special case, the approach is general and can be applied to other classes of sources of practical interest.