Resilient transmission of H.264/AVC video sequences using probabilistic neural networks

H.264/AVC is expected to become an essential component in the delivery of wireless multimedia content. While achieving high compression ratios, this codec is extremely vulnerable to transmission errors. These errors generally result in spatio-temporal propagation of distorted macroblocks (MBs) which significantly degrade the perceptual quality of the reconstructed video sequences. This paper presents a scheme for resilient transmission of H.264/AVC streams in noisy environments. The proposed algorithm exploits the redundant information which is inherent in the neighboring MBs and applies a probabilistic neural network (PNN) classifier to detect visually impaired MBs. This algorithm achieves peak signal-to-noise ratio (PSNR) gains of up to 14.29 dB when compared to the standard decoder. Moreover, this significant gain in quality is achieved with minimal overheads and no additional bandwidth requirement, thus making it suitable for conversational and multicast/ broadcast services where feedback-based transport protocols cannot be applied.

[1]  Markus Rupp,et al.  Performance of a H.264/AVC Error Detection Algorithm Based on Syntax Analysis , 2007, J. Mobile Multimedia.

[2]  Cyril Bergeron,et al.  Soft-input decoding of variable-length codes applied to the H.264 standard , 2004, IEEE 6th Workshop on Multimedia Signal Processing, 2004..

[3]  Jin-Jang Leou,et al.  Detection and concealment of transmission errors in MPEG-2 images-a genetic algorithm approach , 1999, IEEE Trans. Circuits Syst. Video Technol..

[4]  Reuben A. Farrugia,et al.  ENHANCING ERROR RESILIENCE IN WIRELESS TRANSMITTED COMPRESSED VIDEO SEQUENCES THROUGH A PROBABILISTIC NEURAL NETWORK CORE , 2007 .

[5]  Miska M. Hannuksela,et al.  H.264/AVC video for wireless transmission , 2005, IEEE Wireless Communications.

[6]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[7]  Stephan Wenger,et al.  H.264/AVC over IP , 2003, IEEE Trans. Circuits Syst. Video Technol..

[8]  Timo Hämäläinen,et al.  Detecting corrupted intra macroblocks in H.263 video , 2002, 2002 IEEE Workshop on Multimedia Signal Processing..

[9]  Ekram Khan,et al.  Iterative error detection and correction of H.263 coded video for wireless networks , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Linh Viet Tran,et al.  Efficient Image Retrieval with Statistical Color Descriptors , 2003 .

[11]  David G. Stork,et al.  Pattern Classification , 1973 .

[12]  Markus Rupp,et al.  Robust Error Detection for H.264/AVC Using Relation Based Fragile Watermarking , 2006 .

[13]  Markus Rupp,et al.  Improved Detection for H.264 Encoded Video Sequences over Mobile Networks , 2005 .

[14]  Miska M. Hannuksela,et al.  H.264/AVC in wireless environments , 2003, IEEE Trans. Circuits Syst. Video Technol..

[15]  Olivia Nemethova,et al.  Combined sequential decoding and error concealment of H.264 video , 2004, IEEE 6th Workshop on Multimedia Signal Processing, 2004..

[16]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[17]  Xinggang Lin,et al.  Content based error detection and concealment for image transmission over wireless channel , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..