The Experts below are selected from a list of 12 Experts worldwide ranked by ideXlab platform
Ioan Tabus - One of the best experts on this subject based on the ideXlab platform.
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Patch-Based Conditional Context Coding of Stereo Disparity Images
2015Co-Authors: Ioan Tabus, Senior MemberAbstract:Abstract—This letter proposes a method for lossless coding the left disparity image, L, from a stereo disparity image pair (L,R), conditional on the right disparity image, R, by keeping track of the transformation of the constant patches fromR to L. The disparities in R are used for predicting the disparities in L, and the locations of the pixels where the prediction is erroneous are encoded in a first stage, conditional on the patch-labels of R image, allowing the de-coder to already reconstruct with certainty some elements of the L image, e.g., the disparity values at certain pixels and parts of the contours of left image patches. Second, the contours of the patches in L image that are still unknown after first stage are condition-ally encoded using a mixed conditioning context: the usual causal current context from the contours of L and a noncausal context ex-tracted from the contours in the correctly estimated part of L ob-tained in the first stage. The depth values in the patches of L image are finally encoded, if they are not already known from the pre-diction stage. The new algorithm, dubbed conditional Crack-Edge Region value (C-CERV), is shown to perform significantly better than the non-conditional coding method CERV and than another existing conditional coding method, over the Middlebury corpus. C-CERV is shown to reach lossless compression ratios of 100-250 times for those images that have a high precision of the disparity map. Index Terms—Arithmetic coding, context tree coding, inter-coding, lossless disparity image compression. I
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Patch-Based Conditional Context Coding of Stereo Disparity Images
IEEE Signal Processing Letters, 2014Co-Authors: Ioan TabusAbstract:This letter proposes a method for lossless coding the left disparity image, L, from a stereo disparity image pair (L,R), conditional on the right disparity image, R, by keeping track of the transformation of the constant patches from R to L. The disparities in R are used for predicting the disparities in L, and the locations of the pixels where the prediction is erroneous are encoded in a first stage, conditional on the patch-labels of R image, allowing the decoder to already reconstruct with certainty some elements of the L image, e.g., the disparity values at certain pixels and parts of the contours of left image patches. Second, the contours of the patches in L image that are still unknown after first stage are conditionally encoded using a mixed conditioning context: the usual causal current context from the contours of L and a noncausal context extracted from the contours in the correctly estimated part of L obtained in the first stage. The depth values in the patches of L image are finally encoded, if they are not already known from the prediction stage. The new algorithm, dubbed conditional Crack-Edge Region value (C-CERV), is shown to perform significantly better than the non-conditional coding method CERV and than another existing conditional coding method, over the Middlebury corpus. C-CERV is shown to reach lossless compression ratios of 100-250 times for those images that have a high precision of the disparity map.
L. M. Brock - One of the best experts on this subject based on the ideXlab platform.
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Transient thermal effects in Edge dislocation generation near a Crack Edge
International Journal of Solids and Structures, 1992Co-Authors: L. M. BrockAbstract:Abstract A transient 2-D study of Edge dislocation generation near a Crack in a fully-coupled thermoelastic solid loaded by SV-wave diffraction is considered. Exact solutions to the mixed boundary/initial value problem in the integral transform space are obtained, and inversions valid for short times performed. The solution behavior indicates that the generation process requires only a short time period, and that thermal effects might be important. In particular, a thermally-sensitive dislocation takes longer to be emitted from the Crack Edge Region than one described in a non-thermal analysis but. on the other hand, does not arrest. Moreover, in contrast to the simple relaxation effect seen in non-thermal analyses, dislocation generation here causes oscillations in the dynamic stress intensity factor. Finally, the average temperature gradient across the dislocation cut is large enough to suggest that generation may be a potential source of local material disorder.
Senior Member - One of the best experts on this subject based on the ideXlab platform.
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Patch-Based Conditional Context Coding of Stereo Disparity Images
2015Co-Authors: Ioan Tabus, Senior MemberAbstract:Abstract—This letter proposes a method for lossless coding the left disparity image, L, from a stereo disparity image pair (L,R), conditional on the right disparity image, R, by keeping track of the transformation of the constant patches fromR to L. The disparities in R are used for predicting the disparities in L, and the locations of the pixels where the prediction is erroneous are encoded in a first stage, conditional on the patch-labels of R image, allowing the de-coder to already reconstruct with certainty some elements of the L image, e.g., the disparity values at certain pixels and parts of the contours of left image patches. Second, the contours of the patches in L image that are still unknown after first stage are condition-ally encoded using a mixed conditioning context: the usual causal current context from the contours of L and a noncausal context ex-tracted from the contours in the correctly estimated part of L ob-tained in the first stage. The depth values in the patches of L image are finally encoded, if they are not already known from the pre-diction stage. The new algorithm, dubbed conditional Crack-Edge Region value (C-CERV), is shown to perform significantly better than the non-conditional coding method CERV and than another existing conditional coding method, over the Middlebury corpus. C-CERV is shown to reach lossless compression ratios of 100-250 times for those images that have a high precision of the disparity map. Index Terms—Arithmetic coding, context tree coding, inter-coding, lossless disparity image compression. I
K. B. Broberg - One of the best experts on this subject based on the ideXlab platform.
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Cracks and fracture
1999Co-Authors: K. B. BrobergAbstract:"Cracks and Fracture" consists of nine chapters in logical sequence. In two introductory chapters, physical processes in the vicinity of the Crack Edge are discussed and the fracture process is described. Chapter 3 develops general basic concepts and relations in Crack mechanics, such as path independent integrals, stress intensity factors and energy flux into the Crack Edge Region. Chapters 4-7 deal with elastostatic Cracks, stationary or slowly moving elastic-plastic Cracks, elastodynamic Crack mechanics and elastoplastic aspects of fracture, including dynamic fracture mechanics. Appendices include general formulae, the basic theory of analytic functions, introduction to Laplace and Hankel transforms and description of certain basic relations, for instance for stress waves in solids. There is an extensive bibliography, containing references to both classical and recent work, and a comprehensive index. It presents an extensive bibliography containing references to both classical and recent works and a comprehensive index. Appendices include general formulas, the basic theory of analytic functions, introduction to Laplace and Hankel transforms, and descriptions of certain basic relations, for instance for stress waves in solids.
