Robust transmission of H.264/AVC sequences using list decoding and source constraints

Abstract

Abstract-Video compression standards commonly adopted in wireless multimedia transmission systems generally apply variable length codes (VLCs) to achieve the required datarates. The resulting bitstreams are sensitive to transmission errors which cause visual artifacts that propagate in both spatial and temporal domains, thus reducing significantly the quality of the reconstructed video sequences. This paper proposes the application of a List Decoder to improve the quality of H.264/AVC encoded sequences. This method relies on sequence estimation and residual source redundancies to recover feasible images. The recovered images may still contain errors which may cause visually distorted macroblocks (MBs). Therefore, the Average Intersample Difference across Boundaries (AIDB) metric was used to detect these visually impaired MBs at pixel level which are then adequately concealed. Simulation results show that the proposed algorithm manages to achieve Peak Signal-to-Noise (PSNR) gains of up to 2.17 dB when compared to the conventional decoding method. The proposed solution is fully compatible with the H.264/AVC standard and no additional bandwidth is required. Index Terms-Error correction coding, error resilient coding, H.264/AVC, video coding, wireless video transmission. I. INTRODUCTIONULTIMEDIA communication services necessitate efficient video compression standards in order to deliver high quality content within limited bandwidths. H.264/AVC seems to be an attractive candidate for all wireless video applications mainly because of its enhanced compression efficiency and network friendly design [1]. However, it is sensitive to transmission errors, which are common in wireless environments, where a single corrupted bit may cause visual distortions which will significantly reduce the perceptual quality of the reconstructed video sequence.A feedback channel, commonly used for reliable data transmission, cannot be adopted in typical conversational and multicast/broadcast applications because of delay constraints and the unavailability of the feedback channel respectively. Moreover, low bit-rate and low delay applications generally adopt the baseline profile which has limited error-resilient mechanisms [2], [3].In order to solve these problems, a number of errorresilient mechanisms were proposed in literature. authors have applied syntax analysis in order to detect corrupted macroblocks (MBs). However, this method only manages to detect 57% of the corrupted MBs. Different error detection and concealment methods have been proposed which exploit the inherent redundancies within and outside an MB [5] -[7] at pixel level. However, these features achieve low detection rates when applied individually. To alleviate this problem, the authors in [8] have combined a set of pixel level features and applied heuristic thresholds. They have also applied an iterative error correction algorithm which has achieved a significant gain in Peak Signal-to-Noise Ratio (PSNR) at the expense of a significant increase in complexity, which makes ...

Robust Video Transmission Using Reversible Watermarking Techniques

“…In [7], syntax and semantic violation rules were proposed which only manage to locate 57% of the visually impaired regions. Joint Source-Channel techniques were adopted in [8] - [10]. However, the method proposed in [8] reduces the compression efficiency of the codec while the other approaches provide limited protection.…”

Robust decoder-based error control strategy for recovery of H.264/AVC video content

“…The redundancy in the compressed image and video was analysed in [30], where it was concluded that significant gain in performance can be achieved when additional video data properties are taken into consideration while decoding. Based on this observation the authors in [31,32] have implemented a modified Viterbi decoding algorithm to recover feasible video sequences [33]. Sequential decoding methods were adopted for H.264/AVC encoded sequences in [31,34] whose performance in terms of quality is similar to the results presented in [33].…”

“…As shown in Table 2, the sequence cab is present in the list F generated by the list decoder. On the other hand, if the Viterbi approach adopted in [32,33] is performed, this sequence is lost at the expense of sequences having a higher hamming distance from the received bitstream (Table 3). This is mainly because the Viterbi approach selects one partial sequence of k symbols and n bits, thus prematurely pruning a number of potentially valid sequences.…”

Slice error detection and correction decoder for H.264/AVC video sequences

“…Recently, Farrugia and Debono proposed a novel error control strategy based on list decoding, which enables erroneous bits in the video slice to be corrected [5]- [7]. They showed that their method, aided by a slice structuring error resiliency technique and zero motion vector error concealment, is capable of achieving a peak signal-to-noise ratio (PSNR) gain of about 2 dB as compared to one without any error correction [7].…”

“…Analogous to the breadth-first tree search, for a given value of M , the performance of the list decoder is heavily dependent on the length of the decoded sequence as well as the number of possible paths at each stage. The results in [5]- [7] were based on a modest size of 100 bytes per slice. Furthermore, some syntax (stages) have a high number of possible codewords (paths).…”