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In this book we design some high-performance and low-complexity filter banks for multimedia compression and digital communications. We first present a systematic design of the fast approximation of the Discrete Cosine Transform (DCT) using the lifting scheme. A family of fast lapped transforms is then developed, using time-domain pre- and post-processing of the DCT. Compared to the wavelet-based JPEG 2000 standard, our method achieves similar performance with lower complexity. It has been applied into Microsoft/SMPTE VC-1 and JPEG XR standards. Several generalizations are developed next.…mehr

Produktbeschreibung
In this book we design some high-performance and low-complexity filter banks for multimedia compression and digital communications. We first present a systematic design of the fast approximation of the Discrete Cosine Transform (DCT) using the lifting scheme. A family of fast lapped transforms is then developed, using time-domain pre- and post-processing of the DCT. Compared to the wavelet-based JPEG 2000 standard, our method achieves similar performance with lower complexity. It has been applied into Microsoft/SMPTE VC-1 and JPEG XR standards. Several generalizations are developed next. First, we propose a general structure for linear-phase paraunitary filter banks that employs multiple stages of pre- and post-processing of the DCT. Secondly, we investigate the optimal pre- and post-processing for wavelet-based image and video compression. We then introduce an efficient structure for oversampled linear-phase filter banks. Finally, the application of oversampled filter bank in channel equalization is investigated, and a modified Orthogonal Frequency Division Multiplexing (OFDM) scheme is proposed.
Autorenporträt
Jie Liang received the PhD degree from the Johns Hopkins University in 2003. He joined Simon Fraser University, Canada, in 2004, where he is currently an Associate Professor. He was with Microsoft between 2003 and 2004. His research interests include Signal Processing, Information Theory, Digital Communications, and Machine Learning.