Ms. Yingwei Chen Profile

Yingwei Chen

Member Research Staff at Philips Research North America

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Publications (5)

Proceedings Article | 14 March 2005 Paper

Combined data partitioning and fine granularity scalability for channel adaptive video transmission

Karl Wittig, Yingwei Chen, Mihaela van der Schaar

Proceedings Volume 5685, (2005) https://doi.org/10.1117/12.585529

KEYWORDS: Video, Video coding, Computer programming, Video compression, Distortion, Stereolithography, Head, Multimedia, Motion estimation, Image compression

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Proceedings Article | 18 January 2004 Paper

Joint PHY and MAC layer power optimization for video transmission over wireless LAN

Xiaoan Lu, Yingwei Chen, Yao Wang

Proceedings Volume 5308, (2004) https://doi.org/10.1117/12.538251

KEYWORDS: Video, Receivers, Transmitters, Electroluminescence, Signal to noise ratio, Video compression, Local area networks, Received signal strength, Amplifiers, Lutetium

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Proceedings Article | 4 January 2002 Paper

Signal adaptive processing in MPEG-2 decoders with embedded resizing for interlaced video

Zhun Zhong, Yingwei Chen, Tse-Hua Lan

Proceedings Volume 4671, (2002) https://doi.org/10.1117/12.453084

KEYWORDS: Video, Laser induced plasma spectroscopy, Signal processing, Image resolution, Video processing, Data processing, Phase shifts, Bandpass filters, Linear filtering, Computer programming

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Proceedings Article | 19 April 2000 Paper

Embedded DCT and wavelet methods for fine granular scalable video: analysis and comparison

Mihaela van der Schaar-Mitrea, Yingwei Chen, Hayder Radha

Proceedings Volume 3974, (2000) https://doi.org/10.1117/12.382999

KEYWORDS: Wavelets, Signal to noise ratio, Transform theory, Video, Internet, Statistical analysis, Wavelet transforms, Image compression, Video compression, Signal analysis

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Video transmission over bandwidth-varying networks is becoming increasingly important due to emerging applications such as streaming of video over the Internet. The fundamental obstacle in designing such systems resides in the varying characteristics of the Internet (i.e. bandwidth variations and packet-loss patterns). In MPEG-4, a new SNR scalability scheme, called Fine-Granular-Scalability (FGS), is currently under standardization, which is able to adapt in real-time (i.e. at transmission time) to Internet bandwidth variations. The FGS framework consists of a non-scalable motion-predicted base-layer and an intra-coded fine-granular scalable enhancement layer. For example, the base layer can be coded using a DCT-based MPEG-4 compliant, highly efficient video compression scheme. Subsequently, the difference between the original and decoded base-layer is computed, and the resulting FGS-residual signal is intra-frame coded with an embedded scalable coder. In order to achieve high coding efficiency when compressing the FGS enhancement layer, it is crucial to analyze the nature and characteristics of residual signals common to the SNR scalability framework (including FGS). In this paper, we present a thorough analysis of SNR residual signals by evaluating its statistical properties, compaction efficiency and frequency characteristics. The signal analysis revealed that the energy compaction of the DCT and wavelet transforms is limited and the frequency characteristic of SNR residual signals decay rather slowly. Moreover, the blockiness artifacts of the low bit-rate coded base-layer result in artificial high frequencies in the residual signal. Subsequently, a variety of wavelet and embedded DCT coding techniques applicable to the FGS framework are evaluated and their results are interpreted based on the identified signal properties. As expected from the theoretical signal analysis, the rate-distortion performances of the embedded wavelet and DCT-based coders are very similar. However, improved results can be obtained for the wavelet coder by deblocking the base- layer prior to the FGS residual computation. Based on the theoretical analysis and our measurements, we can conclude that for an optimal complexity versus coding-efficiency trade- off, only limited wavelet decomposition (e.g. 2 stages) needs to be performed for the FGS-residual signal. Also, it was observed that the good rate-distortion performance of a coding technique for a certain image type (e.g. natural still-images) does not necessarily translate into similarly good performance for signals with different visual characteristics and statistical properties.

Proceedings Article | 27 February 1996 Paper

Three-dimensional subband coding of video using the zero-tree method

Yingwei Chen, William Pearlman

Proceedings Volume 2727, (1996) https://doi.org/10.1117/12.233203

KEYWORDS: Video coding, Image compression, Video, 3D image processing, Video compression, Distortion, Solids, Image transmission, Silicon, Computer programming

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