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%.

[1]  D. F. Specht,et al.  Probabilistic neural networks for classification, mapping, or associative memory , 1988, IEEE 1988 International Conference on Neural Networks.

[2]  Information technology — Generic coding of moving pictures and associated audio information — Part 2 : Video Technologies , 2022 .

[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]  Jin-Jang Leou,et al.  Detection and concealment of transmission errors in H.261 images , 1998, IEEE Trans. Circuits Syst. Video Technol..

[5]  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.

[6]  Jiangtao Wen,et al.  Reversible variable length codes for robust image and video transmission , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[7]  Itu-T.  Video coding for low bitrate communication , 1996 .

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

[9]  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..

[10]  Mark R. Pickering,et al.  A statistical error detection technique for low bit-rate video , 1997, TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162).

[11]  Byeungwoo Jeon,et al.  Error detection and recovery by hiding information into video bitstream using fragile watermarking , 2002, IS&T/SPIE Electronic Imaging.

[12]  C.J. Debono,et al.  Enhancing the Error Detection Capabilities of DCT Based Codecs using Compressed Domain Dissimilarity Metrics , 2007, EUROCON 2007 - The International Conference on "Computer as a Tool".

[13]  Jin-Jang Leou,et al.  Detection and correction of transmission errors in JPEG images , 1998, IEEE Trans. Circuits Syst. Video Technol..

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

[15]  C.J. Debono,et al.  Enhancing the Error Detection Capabilities of the Standard Video Decoder using Pixel Domain Dissimilarity Metrics , 2007, EUROCON 2007 - The International Conference on "Computer as a Tool".

[16]  Reuben A. Farrugia,et al.  A Statistical Bit Error Generator for Emulation of Complex Forward Error Correction Schemes , 2007, 2007 IEEE International Conference on Communications.