Error correction by means of arithmetic codes: an application to resilient image transmission (original) (raw)
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Joint Source/Channel Coding and MAP Decoding of Arithmetic Codes
IEEE Transactions on Communications, 2005
In this paper, a novel maximum a posteriori (MAP) estimation approach is employed for error correction of arithmetic codes with a forbidden symbol. The system is founded on the principle of joint source channel coding, which allows one to unify the arithmetic decoding and error correction tasks into a single process, with superior performance compared to traditional separated techniques. The proposed system improves the performance in terms of error correction with respect to a separated source and channel coding approach based on convolutional codes, with the additional great advantage of allowing complete flexibility in adjusting the coding rate. The proposed MAP decoder is tested in the case of image transmission across the additive white Gaussian noise channel and compared against standard forward error correction techniques in terms of performance and complexity. Both hard and soft decoding are taken into account, and excellent results in terms of packet error rate and decoded image quality are obtained.
IEEE Transactions on Image Processing, 2003
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.
Joint source/channel coding using arithmetic codes
IEEE Transactions on Communications, 2001
Reserving space for a symbol that is not in the source alphabet has been shown to provide excellent error detection. In this paper, we show how to exploit this capability using two sequential decoder structures to provide powerful error correction capability. This joint source/channel coder design provides significant packet loss recovery with minimal rate overhead, and compares favorably with conventional schemes.
Applications of Error-Control Coding
IEEE Transactions on Information Theory, 1998
An overview of the many practical applications of channel coding theory in the past 50 years is presented. The following application areas are included: deep space communication, satellite communication, data transmission, data storage, mobile communication, file transfer, and digital audio/video transmission. Examples, both historical and current, are given that typify the different approaches used in each application area. Although no attempt is made to be comprehensive in our coverage, the examples chosen clearly illustrate the richness, variety, and importance of error-control coding methods in modern digital applications.
The far end error decoder with application to image transmission
GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270), 2001
We present two new decoding algorithms that estimate the output (path in the trellis) of a Markov source observed through a discrete memoryless channel with special application to convolutional codes. In a change of paradigm, these decoders do not exclusively aim on a low average error probability, but rather try to maximize the contiguously correct decoded subpath (where a subpath begins with the first symbol)-a concept termed Far End Error Decoding. In addition to path estimation, these decoders provide a reliability about each subpath and, thus, enable us to localize the first decoding error without spending additional redundancy. This approach is motivated by the fact that in many applications it is much more important to deliver only error free data to the source decoder rather than to achieve a low error probability. The significant performance gain possible with this new approach is demonstrated for the example of SPIHT coded images.
Combined error protection and compression using turbo codes for error resilient image transmission
2005
Abstract A joint source channel coding scheme for error resilient image transmission is proposed. A practical image coder was introduced in AN Kim et al,(2004) using modified differential pulse coded modulation (DPCM) codec with multi-rate processing and adaptive entropy coding. In this paper the residual redundancy of the prediction error image is exploited by using turbo codes for both data compression and error protection.
Unequal Error Protection for ROI Coded Images over Fading Channels
2005 Systems Communications (ICW'05, ICHSN'05, ICMCS'05, SENET'05), 2005
Region of interest (ROI) coding is a feature supported by the Joint Photographic Experts Group 2000 (JPEG2000) image compression standard and allows particular regions of interest within an image to be compressed at a higher quality than the rest of the image. In this paper, unequal error protection (UEP) is proposed for ROI coded JPEG2000 images as a technique for providing increased resilience against the effects of transmission errors over a wireless communications channel. The hierarchical nature of an ROI coded JPEG2000 code-stream lends itself to the use of UEP whereby the important bits of the code-stream are protected with a strong code while the less important bits are protected with a weaker code. Simulation results obtained using symbol-by-symbol maximum a posteriori probability (MAP) decoding demonstrate that the use of UEP offers significant gains in terms of the peak signal to noise ratio (PSNR) and the percentage of readable files. Moreover, the use of ROI-based UEP leads to reduced computational complexity at the receiver.
A Joint Source Channel Decoding for Image Transmission
Advances in Science, Technology and Engineering Systems Journal
In this paper, we present a joint source-channel decoding (JSCD) scheme for image transmission. The binary sequences, resulting from the compression of several number of image blocks using arithmetic coding (AC), are written line-wise in the so called readmatrix (RM). In succession, a systematic Low Density Parity Check (LDPC) encoding is applied to the sequence produced by the column-wise reading of the RM. The proposed approach to JSCD incorporates error-free AC-decoder information feedback and errordetection AC-decoder information feedback in each sub-sequence. An error resilience (ER) technique within AC provides whether the input sequence is correct or not and possibly identifies the corrupt segment. In case of error detection, the reliabilities of the bits in the AC decoder input stream are estimated involving the detection delay distribution of the erroneous symbols. This information is provided to the iterative LDPC decoder after a bit back-tracking stage. Experimental results show that the proposed JSCD scheme outperforms the separated source-channel model and reduces the number of decoding iterations.
IEEE Signal Processing Magazine, 2000
T he growing importance of the Internet and the development of new communication devices such as 3G mobile phones have raised interest in robust image communication systems over unreliable channels. Error control can be achieved with forward error correction (FEC), error concealment, or error detection and retransmission. This article focuses on FEC for scalable image coders. For various channel models, we survey recent progress made in system design and discuss efficient source-channel bit allocation techniques, with emphasis on unequal error protection.