Enhancing error resilience in wireless transmitted compressed video sequences through a probabilistic neural network core

Video compression standards commonly employed in the delivery of real-time wireless multimedia services regularly adopt variable length codes (VLCs) for efficient transmission. This coding technique achieves the necessary high compression ratios at the expense of an increased system’s vulnerability to transmission errors. The more frequent presence of transmission errors in wireless channels requires video compression standards to accurately detect, localize and conceal any corrupted macroblocks (MBs) present in the video sequence. Unfortunately, standard decoders offer limited error detection and localization capabilities posing a bound on the perceived video quality of the reconstructed video sequence. This paper presents a novel solution which enhances the error detection and localization capabilities of standard decoders through the application of a Probabilistic Neural Network (PNN). The proposed solution generally outperforms other error detection mechanisms present in literature, as it manages to improve the standard decoder’s error detection rate by up to 95.74%. Index Terms — Error detection coding, learning systems, multimedia communications, video coding, wireless networks.peer-reviewe

Enhancing the error detection capabilities of DCT based codecs using compressed domain dissimilarity metrics

Video compression standards are implemented in wireless data transmission technologies to provide multimedia services efficiently. These compression standards generally utilize the Discrete Cosine Transform (DCT) in conjunction with variable length codes (VLC) in order to achieve the required high compression ratios. While providing the necessary high data rates, this technique has the disadvantage of making the system more susceptible to transmission errors. The standard decoders do not manage to detect a large number of corrupted macroblocks, 40.54% not detected for H.263+, contributing to a significant reduction in the end-to-end video quality as perceived by the end-user. This paper presents three dissimilarity metrics which contain both color and texture information and that can be extracted directly from the compressed DCT coefficients. These metrics can be used to enhance the error-detection capabilities of standard DCT based codecs. Simulation results show that the proposed algorithm increases the error detection rate by 54.06% with a gain in peak signal-to-noise ratio (PSNR) of 3.21 dB. This improvement in performance is superior to other solutions found in literature.peer-reviewe

Robust video transmission using reversible watermarking techniques

This paper presents a novel error-resilient strategy which employs a reversible watermarking technique to protect the H.264/AVC video content. The proposed scheme adopts reversible watermarking to embed an error detection codeword within every Macro block (MB). The watermark is then extracted at the decoder and used to detect the corrupted MBs to be concealed. The proposed scheme further manages to recover the original video content after watermark extraction, thus providing no loss in video quality. The simulation results demonstrate that the proposed approach provides a substantial gain of up to 2.6 dB in Peak Signal-to-Noise Ratio (PSNR) relative to the standard with a minimal increase in complexity.peer-reviewe

Enhancing the error detection capabilities of the standard video decoder using pixel domain dissimilarity metrics

The video compression standards commonly adopted in wireless multimedia services utilize variable length codes (VLC) in order to attain high compression ratios. While providing the high data rates required, this technique makes the system more susceptible to transmission errors. Thus the end-to-end quality of the video stream transmitted over an error-prone channel depends on the detection, and concealment of the corrupted macroblocks. The error detection capability of standard decoders is quite limited, for example, in the case of the H.263+ codec around 40.54% of the corrupted macroblocks are undetected, placing a bound on the perceived quality of the reconstructed video sequence. This paper presents a novel solution using eight pixel domain dissimilarity metrics computed in the CIE LUV color space which can be used at decode time to improve the error detection rate of the standard decoder. The spatial dissimilarity metric has been found to perform the best with an average increase in error detection rate of 60.38% when compared to the standard decoder (about 20% more than other published results) with 0% of false detection and a gain in peak signal-to-noise ratio (PSNR) of 3.94 dB.peer-reviewe

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

Real-time wireless conversational and broadcasting multimedia applications offer particular transmission challenges as reliable content delivery cannot be guaranteed. The undelivered and erroneous content causes significant degradation in quality of experience. The H.264/AVC standard includes several error resilient tools to mitigate this effect on video quality. However, the methods implemented by the standard are based on a packet-loss scenario, where corrupted slices are dropped and the lost information concealed. Partially damaged slices still contain valuable information that can be used to enhance the quality of the recovered video. This study presents a novel error recovery solution that relies on a joint source-channel decoder to recover only feasible slices. A major advantage of this decoder-based strategy is that it grants additional robustness while keeping the same transmission data rate. Simulation results show that the proposed approach manages to completely recover 30.79% of the corrupted slices. This provides frame-by-frame peak signal-to-noise ratio (PSNR) gains of up to 18.1%dB, a result which, to the knowledge of the authors, is superior to all other joint source-channel decoding methods found in literature. Furthermore, this error resilient strategy can be combined with other error resilient tools adopted by the standard to enhance their performance.peer-reviewe