The Experts below are selected from a list of 75852 Experts worldwide ranked by ideXlab platform
J W Havlicek - One of the best experts on this subject based on the ideXlab platform.
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coperm Transform Domain energy compaction by optimal permutation
IEEE Transactions on Signal Processing, 1999Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:Compaction by optimal permutation (COPERM) is a tool for Transform Domain energy compaction of broadband signals, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable (e.g., from a Transform-Domain compaction viewpoint) signal from a class of "target" signals (e.g., DCT basis functions) by means of a suitable permutation of its samples. One application of Transform-Domain energy compaction is in lossy compression. We pursue one possible thread in detail and demonstrate some interesting broadband image compression results.
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coperm Transform Domain energy compaction by optimal permutation
International Conference on Acoustics Speech and Signal Processing, 1998Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:COPERM is a novel paradigm for energy compaction and signal compression, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable signal from a class of "target" signals, by means of a suitable permutation of its samples. The approach is well-suited for Transform Domain energy compaction prior to Transform-Domain compression of persistent broadband signals. The associated optimal permutation precoders are surprisingly simple, and the permutation precoding overhead can be made modest-resulting in improved overall rate-distortion performance.
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ICASSP - COPERM: Transform-Domain energy compaction by optimal permutation
Proceedings of the 1998 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP '98 (Cat. No.98CH36181), 1Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:COPERM is a novel paradigm for energy compaction and signal compression, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable signal from a class of "target" signals, by means of a suitable permutation of its samples. The approach is well-suited for Transform Domain energy compaction prior to Transform-Domain compression of persistent broadband signals. The associated optimal permutation precoders are surprisingly simple, and the permutation precoding overhead can be made modest-resulting in improved overall rate-distortion performance.
Homer H. Chen - One of the best experts on this subject based on the ideXlab platform.
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Rounding Mismatch Between Spatial-Domain and Transform-Domain Video Codecs
IEEE Transactions on Circuits and Systems for Video Technology, 2006Co-Authors: Chen Chen, Homer H. ChenAbstract:The mismatch between a spatial-Domain encoder and a Transform-Domain decoder due to rounding can cause serious video quality degradation after a series of inter-coded frames. The mismatch is rooted on the fact that rounding is a nonlinear operation, and hence its equivalent in the Transform Domain does not exist. We analyze the mathematical property of the rounding operation and propose a practical solution that provides an optimal approximation of the rounding operation in the Transform-Domain. The proposed solution is able to reduce the mismatch and preserve image quality. Experimental results are shown to demonstrate the effectiveness of the solution
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EUSIPCO - A practical solution to Transform-Domain rounding
2005Co-Authors: Chen Chen, Homer H. ChenAbstract:In many multimedia applications, manipulation of video signals is preferably performed in the Transform Domain. Most of such operations are derived from their counterparts in the pixel Domain. However, the rounding operation can not be obtained this way because it is a nonlinear operation. Without a proper treatment, it may become a major source of errors for multimedia systems, causing a mismatch between the encoder and the decoder. This problem seems to have been largely ignored. In this paper, we propose a practical solution to this problem by a thorough examination of the mathematical property of the rounding error in the context of Transform-Domain video transcoding and demonstrate its performance.
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ISCAS (2) - Transform-Domain intra prediction for H.264
2005 IEEE International Symposium on Circuits and Systems, 1Co-Authors: Chen Chen, Homer H. ChenAbstract:H.264/AVC is the newest video coding standard jointly developed by the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. In contrast to some previous coding standards such as H.263+ and MPEG-4 Part-2, where intra prediction is performed in the Transform Domain, the intra prediction of H.264 is completely defined in the pixel Domain. This presents a challenge to multimedia systems in which transcoding is conducted in the Transform Domain for the purpose of computational efficiency. In this paper, we show how to obtain the Transform Domain predictions for various intra modes of H264. We begin by converting the intra prediction from the pixel Domain to the Transform Domain through matrix manipulation. Then we show how the operations involved in the matrix manipulation can be simplified. A computational complexity analysis of each intra prediction mode of H.264 is provided.
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A practical solution to Transform-Domain rounding
2005 International Conference on Wireless Networks Communications and Mobile Computing, 1Co-Authors: Chen Chen, Homer H. ChenAbstract:In many multimedia applications, manipulation of video signals is preferably performed in the Transform Domain. Most of such operations are derived from their counterparts in the pixel Domain. However, the rounding operation can not be obtained this way because it is a nonlinear operation. Without a proper treatment, it may become a major source of errors for multimedia systems, causing a mismatch between the encoder and the decoder. This problem seems to have been largely ignored. In this paper, we propose a practical solution to this problem by a thorough examination of the mathematical property of the rounding error in the context of Transform-Domain video transcoding and demonstrate its performance.
N D Sidiropoulos - One of the best experts on this subject based on the ideXlab platform.
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coperm Transform Domain energy compaction by optimal permutation
IEEE Transactions on Signal Processing, 1999Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:Compaction by optimal permutation (COPERM) is a tool for Transform Domain energy compaction of broadband signals, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable (e.g., from a Transform-Domain compaction viewpoint) signal from a class of "target" signals (e.g., DCT basis functions) by means of a suitable permutation of its samples. One application of Transform-Domain energy compaction is in lossy compression. We pursue one possible thread in detail and demonstrate some interesting broadband image compression results.
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coperm Transform Domain energy compaction by optimal permutation
International Conference on Acoustics Speech and Signal Processing, 1998Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:COPERM is a novel paradigm for energy compaction and signal compression, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable signal from a class of "target" signals, by means of a suitable permutation of its samples. The approach is well-suited for Transform Domain energy compaction prior to Transform-Domain compression of persistent broadband signals. The associated optimal permutation precoders are surprisingly simple, and the permutation precoding overhead can be made modest-resulting in improved overall rate-distortion performance.
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ICASSP - COPERM: Transform-Domain energy compaction by optimal permutation
Proceedings of the 1998 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP '98 (Cat. No.98CH36181), 1Co-Authors: N D Sidiropoulos, Marios S Pattichis, Alan C Bovik, J W HavlicekAbstract:COPERM is a novel paradigm for energy compaction and signal compression, whose foundation is a simple but powerful idea: any signal can be Transformed to resemble a more desirable signal from a class of "target" signals, by means of a suitable permutation of its samples. The approach is well-suited for Transform Domain energy compaction prior to Transform-Domain compression of persistent broadband signals. The associated optimal permutation precoders are surprisingly simple, and the permutation precoding overhead can be made modest-resulting in improved overall rate-distortion performance.
P C Ching - One of the best experts on this subject based on the ideXlab platform.
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on the optimality of convergence behaviour for Transform Domain split path adaptive filter
International Conference on Acoustics Speech and Signal Processing, 1994Co-Authors: K F Wan, P C ChingAbstract:A fast LMS adaptive filtering algorithm in Transform-Domain is developed. The algorithm is applied to a structure which decomposed an adaptive FIR filter into a parallel connection of two subfilters, one with a symmetric property and the other with an antisymmetric property. A detail analysis on the optimality of the convergence behaviour for this Transform-Domain split-path adaptive filter is presented. Simulation results show that the proposed algorithm has superior convergence performance while the increase in computation is only modest. >
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Transform Domain LMS adaptation of split-path filter
[Proceedings] 1992 IEEE International Symposium on Circuits and Systems, 1Co-Authors: P C Ching, K F WanAbstract:Investigates the application of a Transform Domain adaptive technique to a linear predictor that is configured in a split-path structure. The split-path predictor is composed of two linear phase filters connected in parallel, and thus two matrices are required for LMS (least mean square) adaptation in Transform Domain. An effective way of selecting these matrices is introduced which can provide a significant improvement in the overall performance. Theoretical analysis of the adaptive process and its convergence behavior is given. Computer simulations have demonstrated that, in terms of convergence speed, the proposed system is almost twice as fast as a tapped delay line Transform Domain predictive filter. >
K F Wan - One of the best experts on this subject based on the ideXlab platform.
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on the optimality of convergence behaviour for Transform Domain split path adaptive filter
International Conference on Acoustics Speech and Signal Processing, 1994Co-Authors: K F Wan, P C ChingAbstract:A fast LMS adaptive filtering algorithm in Transform-Domain is developed. The algorithm is applied to a structure which decomposed an adaptive FIR filter into a parallel connection of two subfilters, one with a symmetric property and the other with an antisymmetric property. A detail analysis on the optimality of the convergence behaviour for this Transform-Domain split-path adaptive filter is presented. Simulation results show that the proposed algorithm has superior convergence performance while the increase in computation is only modest. >
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Transform Domain LMS adaptation of split-path filter
[Proceedings] 1992 IEEE International Symposium on Circuits and Systems, 1Co-Authors: P C Ching, K F WanAbstract:Investigates the application of a Transform Domain adaptive technique to a linear predictor that is configured in a split-path structure. The split-path predictor is composed of two linear phase filters connected in parallel, and thus two matrices are required for LMS (least mean square) adaptation in Transform Domain. An effective way of selecting these matrices is introduced which can provide a significant improvement in the overall performance. Theoretical analysis of the adaptive process and its convergence behavior is given. Computer simulations have demonstrated that, in terms of convergence speed, the proposed system is almost twice as fast as a tapped delay line Transform Domain predictive filter. >
