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Abstract The problem of multimedia communications over best-effort networks is addressed here with multiple description coding (MDC) in a distributed framework. In this paper, we first compare four video MDC schemes based on different time splitting patterns and temporal two- or three-band motion-compensated temporal filtering (MCTF). Then, the latter schemes are extended with systematic lossy description coding where the original sequence is separated into two subsequences, one being coded as in the latter schemes, and the other being coded with a Wyner-Ziv (WZ) encoder. This amounts to having a systematic lossy Wyner-Ziv coding of every other frame of each description. This error control approach can be used as an alternative to automatic repeat request (ARQ) or forward error correction (FEC), that is, the additional bitstream can be systematically sent to the decoder or can be requested, as in ARQ. When used as an FEC mechanism, the amount of redundancy is mostly controlled by the quantization of the Wyner-Ziv data. In this context, this approach leads to satisfactory rate-distortion performance at the side decoders, however it suffers from high redundancy which penalizes the central description. To cope with this problem, the approach is then extended to the use of MCTF for the Wyner-Ziv frames, in which case only the low-frequency subbands are WZ-coded and sent in the descriptions.

This paper addresses the problem of video compression for robust transmission on lossy Internet networks. The approach developed relies on multiple description coding (MDC) principles. Predictive multiple description video coding has already been considered for robust video transmission over lossy channels. However, MDC, when combined with motion-compensated prediction, is known to suffer from predictive mismatch: in presence of losses, the prediction signal available at the decoder may differ from the one used at the encoder. In this paper, we describe a video compression scheme based on MDC and Wyner-Ziv (WZ) coding. The input sequence is structured into groups of pictures which contain one key frame and one WZ frame. Each frame is first transformed with a wavelet transform and the resulting frequency bands are quantized with a multiple description scalar quantizer. Two balanced descriptions of the video input are thus generated. The quantization indexes of the WZ frames are coded with an low-density parity-check accumulate-based Slepian-Wolf (SW) coder. The lateral receivers first decode the received key frame lateral descriptions, and then construct the side information needed for decoding the corresponding WZ frame descriptions by motion-compensated interpolation. In the case where the two WZ data descriptions are received, the central decoder can perform a separate SW decoding of the two sequences of quantization indexes. A joint iterative decoding approach of the two WZ descriptions is also described which improve the central WZ data decoding performance, however, at the expense of increased decoding complexity. The influence of the proposed iterative decoding technique and of the amount of redundancy on the lateral and central rate-distortion performance of the algorithm is studied. [ABSTRACT FROM AUTHOR]

This study evaluated the compressibility of multislice CT (MSCT) datasets and its dependence on (1) slice thickness and (2) the use of three-dimensional (3D) vs. 2D JPEG2000 compression methods. Five thoracic CT datasets were obtained using a 16-detector MSCT scanner with a collimation of 0.75 mm (120 kVp, 90 mAs) and reconstructed at five slice thicknesses from 0.75 to 10.0 mm. These datasets were irreversibly compressed using a standard 2D JPEG2000 encoder and a developmental 3D JPEG2000 algorithm based on Part 2 of the JPEG2000 standard. Compression ratios ranged from 4:1 to 64:1. Image distortion was computed utilizing peak signal-to-noise ratio (PSNR) and the Sarnoff JNDmetrix visual discrimination model. For 2D compression, the thinnest sections were substantially less compressible than thicker sections for the same level of image quality, particularly at higher compression ratios. Applying 3D compression yielded consistently higher image quality in most cases compared to 2D compression at the same ratios. The advantage of 3D compression increased for thinner slices and higher compression ratios. These results indicate that 3D JPEG2000 (Part 2) compression offers substantial advantages over the current 2D JPEG2000 standard, yielding better quantitative image quality at similar compression ratios or comparable image quality at higher compression ratios. [Copyright &y& Elsevier]