State Machine Interpretation of Arithmetic Codes for Joint Source and Channel Coding
DCC '06 Proceedings of the Data Compression Conference
A new error resilience technique for image compression using arithmetic coding
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
DCC '09 Proceedings of the 2009 Data Compression Conference
Arithmetic coding-based continuous error detection for efficient ARQ-based image transmission
IEEE Journal on Selected Areas in Communications
The EREC: an error-resilient technique for coding variable-length blocks of data
IEEE Transactions on Image Processing
Iterative Decoding of Serially Concatenated Arithmetic and Channel Codes With JPEG 2000 Applications
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
Motivated by recent results in Joint Source/ Channel JSC coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes AC. A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori MAP sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates PER in the case of transmission on an Additive White Gaussian Noise AWGN channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.