Multiple Description Coding with Side Information: Practical Scheme and Iterative Decoding

Abstract

Multiple description coding (MDC) with side information (SI) at the receiver is particularly relevant for robust transmission in sensor networks where correlated data is being transmitted to a common receiver, as well as for robust video compression. The rate-distortion region for this problem has been established in (Vaishampayan 1993). Here, we focus on the design of a practical MDC scheme with SI at the receiver. It builds upon both MDC principles and Slepian-Wolf (SW) coding principles. The input source is first quantized with a multiple description scalar quantizer (MDSQ) which introduces redundancy or correlation in the transmitted streams in order to take advantage of the path diversity. The resulting sequences of indexes are SW encoded, that is, separately encoded and jointly decoded. While the first step (MDSQ) plays the role of a channel code the second one (SW coding) plays the role of a source code, compressing the sequences of quantized indexes. In a second step, the cross-decoding of the two descriptions is proposed. This allows us to account for both the correlation with the SI as well as the correlation between the two descriptions.

Low‐complexity distributed multiple description coding for wireless video sensor networks

“…This method can achieve rate allocation among different bitplanes. In [37], joint iterative decoding is proposed to improve the decoding performance at the central decoder. Even though the existing DMDC methods can improve the error resilience of DVC in error-prone networks while preserve low encoder complexity criterion essential to DVC, most of these schemes [36][37][38] are based on iteratively decodable channel coding techniques that cause large latencies in the decoding process and require the presence of a feedback channel from the decoder to the encoder.…”

“…As seen in [34][35][36][37][38], incorporating MDC into DVC increases the error resiliency of the DVC in lossy transmission channels. However, there is also an increase in the complexity of the encoder which violates the low-complexity nature of DVC encoders and there is an increase in decoding time which makes real-time video communication difficult.…”

“…In the past few years, numerous MDC schemes for conventional predictive coding have been proposed [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. Recently, several error-resilient video coding techniques that combine the principles of MDC and DVC have been proposed [34][35][36][37][38]. However, technical limitations such as low coding efficiency and long decoding time are still remaining as unsolved problems in these methods.…”

Channel Optimized Distributed Multiple Description Coding

“…Alternatively, we can use (24) and take as the measure of randomness. The CDMD design procedure, with deterministic annealing algorithm, may now be summarized as follows.…”

“…The authors consider the design of multiple description vector quantization (MDVQ) with SI available at the decoder in [23]. In [24], a MD with SI is considered using a non-optimized MDVQ and parity-based turbo codes as the Slepian-Wolf encoders over noiseless channels.…”