The Experts below are selected from a list of 7446 Experts worldwide ranked by ideXlab platform
R.m. Gray - One of the best experts on this subject based on the ideXlab platform.
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Subband-Coded Image reconstruction for lossy packet networks
IEEE Transactions on Image Processing, 1997Co-Authors: S.s. Hemami, R.m. GrayAbstract:Transmission of digital subband-Coded Images over lossy packet networks presents a reconstruction problem at the decoder. This paper presents two techniques for reconstruction of lost subband coefficients, one for low-frequency coefficients and one for high-frequency coefficients. The low-frequency reconstruction algorithm is based on inherent properties of the hierarchical subband decomposition. To maintain smoothness and exploit the high intraband correlation, a cubic interpolative surface is fit to known coefficients to interpolate lost coefficients. Accurate edge placement, crucial for visual quality, is achieved by adapting the interpolation grid in both the horizontal and vertical directions as determined by the edges present. An edge model is used to characterize the adaptation, and a quantitative analysis of this model demonstrates that edges can be identified by simply examining the high-frequency bands, without requiring any additional processing of the low-frequency band. High-frequency reconstruction is performed using linear interpolation, which provides good visual performance as well as maintains properties required for edge placement in the low-frequency reconstruction algorithm. The complete algorithm performs well on loss of single coefficients, vectors, and small blocks, and is therefore applicable to a variety of source coding techniques.
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Subband Coded Image reconstruction for lossy packet networks
Proceedings of 1994 28th Asilomar Conference on Signals Systems and Computers, 1994Co-Authors: S.s. Hemami, R.m. GrayAbstract:Packet-based transmission of subband Coded Images over lossy networks presents a reconstruction problem at the decoder. The paper presents two techniques for reconstruction of lost subband coefficients. The low frequency reconstruction algorithm maintains smoothness and exploits intraband correlation by fitting a surface to known coefficients to interpolate lost coefficients. Accurate edge placement is achieved by warping the interpolation grid based on local high frequency characteristics. High frequency reconstruction is performed using linear interpolation, providing good visual performance and maintaining properties required for edge placement. The algorithm is applicable to any number of decompositions, both luminance and chrominance components, and can be used with progressive transmission. Computational overhead is minimal at 0.5% per percentage of coefficients lost and the reconstructed synthesized Images maintain good visual quality at loss rates as high as 10%.
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Unbalanced tree-growing algorithms for practical Image compression
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: K.l. Oehler, E.a. Riskin, R.m. GrayAbstract:A vector quantization compression system is presented which is suitable for use in commercial applications, i.e., efficient enough to encode a wide variety of Images and simple enough to decode the Images in real time using software (for machine compatibility). A fixed-rate code with unbalanced tree structure is used, and a method of unbalanced tree growing is extended. Simple prediction techniques are applied to improve Coded Image quality.
S.s. Hemami - One of the best experts on this subject based on the ideXlab platform.
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Subband-Coded Image reconstruction for lossy packet networks
IEEE Transactions on Image Processing, 1997Co-Authors: S.s. Hemami, R.m. GrayAbstract:Transmission of digital subband-Coded Images over lossy packet networks presents a reconstruction problem at the decoder. This paper presents two techniques for reconstruction of lost subband coefficients, one for low-frequency coefficients and one for high-frequency coefficients. The low-frequency reconstruction algorithm is based on inherent properties of the hierarchical subband decomposition. To maintain smoothness and exploit the high intraband correlation, a cubic interpolative surface is fit to known coefficients to interpolate lost coefficients. Accurate edge placement, crucial for visual quality, is achieved by adapting the interpolation grid in both the horizontal and vertical directions as determined by the edges present. An edge model is used to characterize the adaptation, and a quantitative analysis of this model demonstrates that edges can be identified by simply examining the high-frequency bands, without requiring any additional processing of the low-frequency band. High-frequency reconstruction is performed using linear interpolation, which provides good visual performance as well as maintains properties required for edge placement in the low-frequency reconstruction algorithm. The complete algorithm performs well on loss of single coefficients, vectors, and small blocks, and is therefore applicable to a variety of source coding techniques.
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Transform Coded Image reconstruction exploiting interblock correlation
IEEE Transactions on Image Processing, 1995Co-Authors: S.s. Hemami, T.h.-y. MengAbstract:Transmission of still Images and video over lossy packet networks presents a reconstruction problem at the decoder. Specifically, in the case of block-based transform Coded Images, loss of one or more packets due to network congestion or transmission errors can result in errant or entirely lost blocks in the deCoded Image. This article proposes a computationally efficient technique for reconstruction of lost transform coefficients at the decoder that takes advantage of the correlation between transformed blocks of the Image. Lost coefficients are linearly interpolated from the same coefficients in adjacent blocks subject to a squared edge error criterion, and the resulting reconstructed coefficients minimize blocking artifacts in the Image while providing visually pleasing reconstructions. The required computational expense at the decoder per reconstructed block is less than 1.2 times a non-recursive DCT, and as such this technique is useful for low power, low complexity applications that require good visual performance.
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Subband Coded Image reconstruction for lossy packet networks
Proceedings of 1994 28th Asilomar Conference on Signals Systems and Computers, 1994Co-Authors: S.s. Hemami, R.m. GrayAbstract:Packet-based transmission of subband Coded Images over lossy networks presents a reconstruction problem at the decoder. The paper presents two techniques for reconstruction of lost subband coefficients. The low frequency reconstruction algorithm maintains smoothness and exploits intraband correlation by fitting a surface to known coefficients to interpolate lost coefficients. Accurate edge placement is achieved by warping the interpolation grid based on local high frequency characteristics. High frequency reconstruction is performed using linear interpolation, providing good visual performance and maintaining properties required for edge placement. The algorithm is applicable to any number of decompositions, both luminance and chrominance components, and can be used with progressive transmission. Computational overhead is minimal at 0.5% per percentage of coefficients lost and the reconstructed synthesized Images maintain good visual quality at loss rates as high as 10%.
T.h.-y. Meng - One of the best experts on this subject based on the ideXlab platform.
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Transform Coded Image reconstruction exploiting interblock correlation
IEEE Transactions on Image Processing, 1995Co-Authors: S.s. Hemami, T.h.-y. MengAbstract:Transmission of still Images and video over lossy packet networks presents a reconstruction problem at the decoder. Specifically, in the case of block-based transform Coded Images, loss of one or more packets due to network congestion or transmission errors can result in errant or entirely lost blocks in the deCoded Image. This article proposes a computationally efficient technique for reconstruction of lost transform coefficients at the decoder that takes advantage of the correlation between transformed blocks of the Image. Lost coefficients are linearly interpolated from the same coefficients in adjacent blocks subject to a squared edge error criterion, and the resulting reconstructed coefficients minimize blocking artifacts in the Image while providing visually pleasing reconstructions. The required computational expense at the decoder per reconstructed block is less than 1.2 times a non-recursive DCT, and as such this technique is useful for low power, low complexity applications that require good visual performance.
Xiao Su - One of the best experts on this subject based on the ideXlab platform.
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Sequence of linear programming for fine-scalable Coded Image transmission with delay bound
IEEE Global Telecommunications Conference 2004. GLOBECOM '04., 2004Co-Authors: Xiao Su, Tao WangAbstract:We study the problem of peer assignment to maximize the quality of transmitting fine-scalable Coded Images on peer-to-peer networks. The requesting peer has a delay constraint to display the Images within a certain delay bound, and it has limited incoming bandwidth. Under these constraints, we first use a simple example to illustrate the peer assignment problem, and then formulate this problem as one linear programming problem and one nonlinear programming problem. Then we propose to solve the second nonlinear problem efficiently using a sequence of linear programming problems. Finally, extensive experiments show the superior performance of our algorithm by comparing it with a nonlinear formulation and with two heuristic schemes.
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Scalable Coded Image transmissions over peer-to-peer networks
2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698), 2003Co-Authors: Xiao Su, R. FatoohiAbstract:In this paper, we study the transmission of scalable Coded Images over peer-to-peer networks. Scalable Coded Images share common prefix of their resulted bit streams even when Coded using different bit rates. This property implies two important consequences on the peer-to-peer system when compared to transmission of non-scalable Coded Images: (1) there exists a many-to-one relationship between supplying and requesting peers as multiple peers with the code Images in different bit rates become eligible as supplying peers; and (2) the set of supplying peers is dynamic over time as the peers in the supplying set may finish transmission at different times. When we transmit the requested Image from multiple supplying peers to a requesting peer, it is very important to design optimal peer assignment algorithms to minimize the overall transmission time for the requesting peer. For this purpose, we first establish a sufficient property for the optimal peer assignment vector, and then design an optimal media segmentation algorithm based on the sufficient property. Finally, we compare the performance of the proposed optimal media segmentation algorithm with two heuristics and verify its superior performance.
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ICME - Scalable Coded Image transmissions over peer-to-peer networks
2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698), 2003Co-Authors: Xiao Su, R. FatoohiAbstract:In this paper, we study the transmission of scalable Coded Images over peer-to-peer networks. Scalable Coded Images share common prefix of their resulted bit streams even when Coded using different bit rates. This property implies two important consequences on the peer-to-peer system when compared to transmission of non-scalable Coded Images: (1) there exists a many-to-one relationship between supplying and requesting peers as multiple peers with the code Images in different bit rates become eligible as supplying peers; and (2) the set of supplying peers is dynamic over time as the peers in the supplying set may finish transmission at different times. When we transmit the requested Image from multiple supplying peers to a requesting peer, it is very important to design optimal peer assignment algorithms to minimize the overall transmission time for the requesting peer. For this purpose, we first establish a sufficient property for the optimal peer assignment vector, and then design an optimal media segmentation algorithm based on the sufficient property. Finally, we compare the performance of the proposed optimal media segmentation algorithm with two heuristics and verify its superior performance.
Hsiaohwa Chen - One of the best experts on this subject based on the ideXlab platform.
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energy constrained distortion reduction optimization for wavelet based Coded Image transmission in wireless sensor networks
IEEE Transactions on Multimedia, 2008Co-Authors: Wei Wang, Dongming Peng, Honggang Wang, Hamid Sharif, Hsiaohwa ChenAbstract:Image transmissions in wireless multimedia sensor networks (WMSNs) are often energy constrained. They also have requirement on distortion minimization, which may be achieved through unequal error protection (UEP) based communication approaches. In related literature with regard to wireless multimedia transmissions, significantly different importance levels between Image-pixel-position information and Image-pixel-value information have not been fully exploited by existing UEP schemes. In this paper, we propose an innovative Image-pixel-position information based resource allocation scheme to optimize Image transmission quality with strict energy budget constraint for Image applications in WMSNs, and it works by exploring these uniquely different importance levels among Image data streams. Network resources are optimally allocated cross PHY, MAC and APP layers regarding inter-segment dependency, and energy efficiency is assured while the Image transmission quality is optimized. Simulation results have demonstrated the effectiveness of the proposed approach in achieving the optimal Image quality and energy efficiency. The performance gain in terms of distortion reduction is especially prominent with strict energy budget constraints and lower Image compression ratios.