The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
John W. Woods - One of the best experts on this subject based on the ideXlab platform.
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motion compensated 3 d Subband coding of video
IEEE Transactions on Image Processing, 1999Co-Authors: Seungjong Choi, John W. WoodsAbstract:This paper describes a video coding system based on motion-compensated three-dimensional (3-D) Subband/wavelet coding (MC-3DSBC), which can overcome the limits of both 3-D SBC and MC prediction-based coding. In this new system, spatio-temporal Subbands are generated by MC temporal analysis and a spatial wavelet transform, and then encoded by 3-D Subband-finite state scalar quantization (3DSB-FSSQ). The rate allocation from the GOP level to each class of Subbands is optimized by utilizing the structural property of MC-3DSBC that additive superposition approximately holds for both rate and distortion. The proposed video coding system is applied to several test video clips. Its performance exceeds that of both a known MPEG-1 implementation and a similar Subband MC predictive coder while maintaining modest computational complexity and memory size.
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Image identification and restoration in the Subband domain
IEEE Transactions on Image Processing, 1994Co-Authors: John W. WoodsAbstract:When faced with a large support point spread function (PSF), the iterative expectation-maximization (EM) algorithm, which is often used for PSF identification, is very sensitive to the initial PSF estimate. To deal with this problem, the authors propose to do EM image identification and restoration in the Subband domain. After the image is first divided into Subbands, the EM algorithm is applied to each Subband separately. Since the PSF can be taken to have smaller support in each Subband, these Subbands should be less of a problem with the EM model identification. They also introduce an adaptive Subband EM method for use in the upper frequency Subbands. >
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Video post-production with compressed images
Smpte Journal, 1994Co-Authors: John W. WoodsAbstract:This article presents new methods for performing two video post-production practices directly on Subband compressed images, i.e., without decoding them first. The first post-production operation is composition of two images, i.e., realizing picture-in-picture. If one simply composes the coded Subbands of two images, ringing and blurring occur because of the spatially rapid switch from one image to the other. To solve this problem, adaptive box borders are introduced that greatly reduce the ringing. The second post-production operation is overlaying text directly into a Subband coded image. Here, only a small section of the image is decoded where the text is to be located, the text is overlaid into this small ima ge fragment, Subbands of the fragment are obtained and seamed into the original Subbands, and the modified fragment is quantized
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Video Post-Production with Compressed Images
SMPTE Journal, 1994Co-Authors: John W. WoodsAbstract:This article presents new methods for performing two video post-production practices directly on Subband compressed images, i.e., without decoding them first. The first post-production operation is composition of two images, i.e., realizing picture-in-picture. If one simply composes the coded Subbands of two images, ringing and blurring occur because of the spatially rapid switch from one image to the other. To solve this problem, adaptive box borders are introduced that greatly reduce the ringing. The second post-production operation is overlaying text directly into a Subband coded image. Here, only a small section of the image is decoded where the text is to be located, the text is overlaid into this small image fragment, Subbands of the fragment are obtained and seamed into the original Subbands, and the modified fragment is quantized. Both operations yield very good to excellent image quality.
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Image identification and restoration in the Subband domain
[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics Speech and Signal Processing, 1992Co-Authors: John W. WoodsAbstract:When faced with a large-sized point spread function, the expectation-maximization (EM) algorithm is very sensitive to local minima. To deal with this problem, it is proposed that EM image identification and restoration be done in the Subband domain. After the image is first divided into Subbands, then the EM algorithm is applied to each Subband separately. In each Subband the point spread function can be modeled by a reduced number of parameters and the image model can be better represented also. An adaptive Subband EM method for quantization of the upper frequency Subbands is introduced. >
Sven Nordholm - One of the best experts on this subject based on the ideXlab platform.
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Minimal Aliasing Subband System Identification
2020Co-Authors: Per Fundin, Jan Mark De Haan, Nedelko Grbic, Ingvar Claesson, Sven NordholmAbstract:Subband adaptive filters have been proposed to avoid the drawbacks of slow convergence and high computational complexity associated with time domain adaptive filters. While the computational complexity is reduced, other undesired properties, such as signal delays and signal aliasing, are introduced. Aliasing effects may result in loss of perception in speech applications. A method for the design of oversampled filter banks is proposed to reduce these effects. The design method aims at reducing the inband aliasing as well as the reconstruction aliasing for the reason of achieving robustness when weighting in the Subbands alters the Subband signal phase and magnitude.
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filter bank design for Subband adaptive microphone arrays
IEEE Transactions on Speech and Audio Processing, 2003Co-Authors: J M De Haan, N Grbic, I Claesson, Sven NordholmAbstract:This paper presents a new method for the design of oversampled uniform DFT-filter banks for the special application of Subband adaptive beamforming with microphone arrays. Since array applications rely on the fact that different source positions give rise to different signal delays, a beamformer alters the phase information of the signals. This in turn leads to signal degradations when perfect reconstruction filter banks are used for the Subband decomposition and reconstruction. The objective of the filter bank design is to minimize the magnitude of all aliasing components individually, such that aliasing distortion is minimized although phase alterations occur in the Subbands. The proposed method is evaluated in a car hands-free mobile telephony environment and the results show that the proposed method offers better performance regarding suppression levels of disturbing signals and much less distortion to the source speech.
N Farvardin - One of the best experts on this subject based on the ideXlab platform.
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comparison of different methods of classification in Subband coding of images
IEEE Transactions on Image Processing, 1997Co-Authors: R L Joshi, Hamid Jafarkhani, J H Kasner, T R Fischer, N Farvardin, Michael W Marcellin, R H BambergerAbstract:This paper investigates various classification techniques, applied to Subband coding of images, as a way of exploiting the nonstationary nature of image Subbands. The advantages of Subband classification are characterized in a rate-distortion framework in terms of "classification gain" and overall "Subband classification gain." Two algorithms, maximum classification gain and equal mean-normalized standard deviation classification, which allow unequal number of blocks in each class, are presented. The dependence between the classification maps from different Subbands is exploited either directly while encoding the classification maps or indirectly by constraining the classification maps. The trade-off between the classification gain and the amount of side information is explored. Coding results for a Subband image coder based on classification are presented. The simulation results demonstrate the value of classification in Subband coding.
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Subband image coding using entropy coded quantization over noisy channels
IEEE Journal on Selected Areas in Communications, 1992Co-Authors: N Tanabe, N FarvardinAbstract:Under the assumption of noiseless transmission the authors develop two entropy-coded Subband image coding schemes. The difference between these schemes is the procedure used for encoding the lowest frequency Subband: predictive coding is used in one system and transform coding in the other. After demonstrating the unacceptable sensitivity of these schemes to transmission noise, the authors also develop a combined source/channel coding scheme in which rate-compatible convolutional codes are used to provide protection against channel noise. A packetization scheme to prevent infinite error propagation is used and an algorithm for optimal assignment of bits between the source and channel encoders of different Subbands is developed. It is shown that, in the presence of channel noise, these channel-optimized schemes offer dramatic performance improvements. >
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Subband image coding using entropy coded quantization over noisy channels
International Conference on Acoustics Speech and Signal Processing, 1990Co-Authors: N Tanabe, N FarvardinAbstract:The design and performance of two entropy-coded Subband image coding schemes are studied. The difference between these schemes is the procedure used for encoding the lowest-frequency Subband; predictive coding is used in one system and transform coding in the other. Other Subbands are encoded using zero-memory quantization. It is shown that, in the absence of channel noise, both schemes perform better than other Subband coding methods. The unacceptable sensitivity of these schemes to transmission noise is demonstrated, and a combined source/channel coding scheme in which rate-compatible punctured convolutional codes are used to provide protection against channel noise is developed. In the presence of channel noise, these channel-optimized schemes offer dramatic performance improvements over schemes designed based on a noiseless-channel assumption. >
Stephane Dupont - One of the best experts on this subject based on the ideXlab platform.
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Subband based speech recognition
International Conference on Acoustics Speech and Signal Processing, 1997Co-Authors: Herve Bourlard, Stephane DupontAbstract:In the framework of hidden Markov models (HMM) or hybrid HMM/artificial neural network (ANN) systems, we present a new approach towards automatic speech recognition (ASR). The general idea is to divide up the full frequency band (represented in terms of critical bands) into several Subbands, compute phone probabilities for each Subband on the basis of Subband acoustic features, perform dynamic programming independently for each band, and merge the Subband recognizers (recombining the respective, possibly weighted, scores) at some segmental level corresponding to temporal anchor points. The results presented in this paper confirm some preliminary tests reported earlier. On both isolated word and continuous speech tasks, it is indeed shown that even using quite simple recombination strategies, this Subband ASR approach can yield at least comparable performance on clean speech while providing better robustness in the case of narrowband noise.
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ICASSP - Subband-based speech recognition
1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997Co-Authors: Herve Bourlard, Stephane DupontAbstract:In the framework of hidden Markov models (HMM) or hybrid HMM/artificial neural network (ANN) systems, we present a new approach towards automatic speech recognition (ASR). The general idea is to divide up the full frequency band (represented in terms of critical bands) into several Subbands, compute phone probabilities for each Subband on the basis of Subband acoustic features, perform dynamic programming independently for each band, and merge the Subband recognizers (recombining the respective, possibly weighted, scores) at some segmental level corresponding to temporal anchor points. The results presented in this paper confirm some preliminary tests reported earlier. On both isolated word and continuous speech tasks, it is indeed shown that even using quite simple recombination strategies, this Subband ASR approach can yield at least comparable performance on clean speech while providing better robustness in the case of narrowband noise.
J M De Haan - One of the best experts on this subject based on the ideXlab platform.
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filter bank design for Subband adaptive microphone arrays
IEEE Transactions on Speech and Audio Processing, 2003Co-Authors: J M De Haan, N Grbic, I Claesson, Sven NordholmAbstract:This paper presents a new method for the design of oversampled uniform DFT-filter banks for the special application of Subband adaptive beamforming with microphone arrays. Since array applications rely on the fact that different source positions give rise to different signal delays, a beamformer alters the phase information of the signals. This in turn leads to signal degradations when perfect reconstruction filter banks are used for the Subband decomposition and reconstruction. The objective of the filter bank design is to minimize the magnitude of all aliasing components individually, such that aliasing distortion is minimized although phase alterations occur in the Subbands. The proposed method is evaluated in a car hands-free mobile telephony environment and the results show that the proposed method offers better performance regarding suppression levels of disturbing signals and much less distortion to the source speech.
