Soft decoding and synchronization of arithmetic codes: application to image transmission over noisy channels

Abstract

Abstract| This paper addresses the issue of robust and joint source-channel decoding of arithmetic codes. We rst analyze dependencies between the variables involved in arithmetic coding by means of the Bayesian formalism. This provides a suitable framework for designing a soft decoding algorithm that provides high error-resilience. It also provides a natural setting for "soft synchronization", i.e., to introduce anchors favoring the likelihood of "synchronized" paths. In order to maintain the complexity o f the estimation within a realistic range, a simple, yet e cient, pruning method is described. The algorithm can be placed in an iterative source-channel decoding structure, in the spirit of serial turbo codes. Models and algorithms are then applied to context-based arithmetic coding widely used in practical systems (e.g. JPEG-2000). Experimentation results with both theoretical sources and with real images coded with JPEG-2000 reveal very good error resilience performances.

Asymptotic Error-Correcting Performance of Joint Source-Channel Schemes based on Arithmetic Coding

“…Howard et al observed that by rounding the interval boundaries, one can noticeably decrease the computational cost of AC without significantly degrading the compression performance. In [6], the table-lookup representation was exploited in order to derive a stochastic automaton which is then followed by a convolutional code. Iterative decoding was used at the receiver side.…”

“…On the other hand, for a memoryless source with a known probability model, the encoder is entirely characterized by the current interval [low, high) and the value of f ollow. Hence, the encoder state can be represented by (low, high, f ollow) as defined in [6]. The idea is thus to precompute all possible states of the arithmetic encoder such that any source stream may be encoded using table lookups rather than arithmetic operations.…”

“…In [8], Demiroglu et al used Trellis Coded Modulation (TCM) jointly with AC; the FS was exploited in order to discard erroneous paths during a List Viterbi decoding process. In [6], Guionnet et al viewed a quasi-arithmetic coder as a state machine where transitions between states were modeled by a Markov process. A symbol-clock and a bit-clock trellis were proposed, and redundancy was added by limiting the number of states and introducing synchronization markers.…”

Accumulator Aided Decoding of Low Complexity SISO Arithmetic Codes with Image Transmission Application

“…Performance is further improved if soft information is iteratively exchanged between source and channel decoder. The proposed schemes in [7], [8], [9], [10] consider state machine representation of arithmetic decoding to apply channel decoding techniques like Viterbi, list-Viterbi, and other sequential search techniques. In [7] stack algorithm and M-algorithm was applied for maximum a posteriori (MAP) error correction decoding of arithmetic codes with forbidden symbol.…”

Iterative Decoding of Serially Concatenated Arithmetic and Channel Codes With JPEG 2000 Applications

“…In particular, in [26], the performance of JPEG 2000 decoding based on MAP and maximum likelihood (ML) metrics is analyzed in the case of transmission across the BSC and the AWGN channel. Soft decoding of arithmetic codes with synchronization marker is studied in [27] and applied to the case of image transmission. It is worth pointing out that the techniques introduced in [25]- [27] are being included in the upcoming Part 11 of the JPEG 2000 standard, which addresses the wireless applications of the novel image coding standard.…”