14 research outputs found
Distributed coding using punctured quasi-arithmetic codes for memory and memoryless sources
This correspondence considers the use of punctured
quasi-arithmetic (QA) codes for the Slepian–Wolf problem. These
entropy codes are defined by finite state machines for memoryless and
first-order memory sources. Puncturing an entropy coded bit-stream leads
to an ambiguity at the decoder side. The decoder makes use of a correlated
version of the original message in order to remove this ambiguity. A
complete distributed source coding (DSC) scheme based on QA encoding
with side information at the decoder is presented, together with iterative
structures based on QA codes. The proposed schemes are adapted to
memoryless and first-order memory sources. Simulation results reveal
that the proposed schemes are efficient in terms of decoding performance
for short sequences compared to well-known DSC solutions using channel
codes.Peer ReviewedPostprint (published version
Analysis on tailed distributed arithmetic codes for uniform binary sources
Distributed Arithmetic Coding (DAC) is a variant of Arithmetic Coding (AC) that can realise Slepian-Wolf Coding (SWC) in a nonlinear way. In the previous work, we defined Codebook Cardinality Spectrum (CCS) and Hamming Distance Spectrum (HDS) for DAC. In this paper, we make use of CCS and HDS to analyze tailed DAC, a form of DAC mapping the last few symbols of each source block onto non-overlapped intervals as traditional AC. We first derive the exact HDS formula for tailless DAC, a form of DAC mapping all symbols of each source block onto overlapped intervals, and show that the HDS formula previously given is actually an approximate version. Then the HDS formula is extended to tailed DAC. We also deduce the average codebook cardinality, which is closely related to decoding complexity, and rate loss of tailed DAC with the help of CCS. The effects of tail length are extensively analyzed. It is revealed that by increasing tail length to a value not close to the bitstream length, closely-spaced codewords within the same codebook can be removed at the cost of a higher decoding complexity and a larger rate loss. Finally, theoretical analyses are verified by experiments
Flexible distribution of complexity by hybrid predictive-distributed video coding
There is currently limited flexibility for distributing complexity in a video coding system. While rate-distortion-complexity (RDC) optimization techniques have been proposed for conventional predictive video coding with encoder-side motion estimation, they fail to offer true flexible distribution of complexity between encoder and decoder since the encoder is assumed to have always more computational resources available than the decoder. On the other hand, distributed video coding solutions with decoder-side motion estimation have been proposed, but hardly any RDC optimized systems have been developed.
To offer more flexibility for video applications involving multi-tasking or battery-constrained devices, in this paper, we propose a codec combining predictive video coding concepts and techniques from distributed video coding and show the flexibility of this method in distributing complexity. We propose several modes to code frames, and provide complexity analysis illustrating encoder and decoder computational complexity for each mode. Rate distortion results for each mode indicate that the coding efficiency is similar. We describe a method to choose which mode to use for coding each inter frame, taking into account encoder and decoder complexity constraints, and illustrate how complexity is distributed more flexibly
Hamming distance spectrum of DAC codes for equiprobable binary sources
Distributed Arithmetic Coding (DAC) is an effective technique for implementing Slepian-Wolf coding (SWC). It has been shown that a DAC code partitions source space into unequal-size codebooks, so that the overall performance of DAC codes depends on the cardinality and structure of these codebooks. The problem of DAC codebook cardinality has been solved by the so-called Codebook Cardinality Spectrum (CCS). This paper extends the previous work on CCS by studying the problem of DAC codebook structure.We define Hamming Distance Spectrum (HDS) to describe DAC codebook structure and propose a mathematical method to calculate the HDS of DAC codes. The theoretical analyses are verified by experimental results
Codebook cardinality spectrum of distributed arithmetic codes for stationary memoryless binary sources
It was demonstrated that, as a nonlinear implementation of Slepian-Wolf Coding, Distributed Arithmetic Coding (DAC) outperforms traditional Low-Density Parity-Check (LPDC) codes for short code length and biased sources. This fact triggers research efforts into theoretical analysis of DAC. In our previous work, we proposed two analytical tools, Codebook Cardinality Spectrum (CCS) and Hamming Distance Spectrum, to analyze DAC for independent and identically-distributed (i.i.d.) binary sources with uniform distribution. This article extends our work on CCS from uniform i.i.d. binary sources to biased i.i.d. binary sources. We begin with the final CCS and then deduce each level of CCS backwards by recursion. The main finding of this article is that the final CCS of biased i.i.d. binary sources is not uniformly distributed over [0, 1). This article derives the final CCS of biased i.i.d. binary sources and proposes a numerical algorithm for calculating CCS effectively in practice. All theoretical analyses are well verified by experimental results
Bridging Hamming Distance Spectrum with Coset Cardinality Spectrum for Overlapped Arithmetic Codes
Overlapped arithmetic codes, featured by overlapped intervals, are a variant
of arithmetic codes that can be used to implement Slepian-Wolf coding. To
analyze overlapped arithmetic codes, we have proposed two theoretical tools:
Coset Cardinality Spectrum (CCS) and Hamming Distance Spectrum (HDS). The
former describes how source space is partitioned into cosets (equally or
unequally), and the latter describes how codewords are structured within each
coset (densely or sparsely). However, until now, these two tools are almost
parallel to each other, and it seems that there is no intersection between
them. The main contribution of this paper is bridging HDS with CCS through a
rigorous mathematical proof. Specifically, HDS can be quickly and accurately
calculated with CCS in some cases. All theoretical analyses are perfectly
verified by simulation results