• Title/Summary/Keyword: Progressive weighting scheme

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Organ Shape Modeling Based on the Laplacian Deformation Framework for Surface-Based Morphometry Studies

  • Kim, Jae-Il;Park, Jin-Ah
    • Journal of Computing Science and Engineering
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    • v.6 no.3
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    • pp.219-226
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    • 2012
  • Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.

Progressive Image Transmission using LOT/CVQ with HVS Weighting (HVS가중치를 갖는 LOT/CVQ를 이용한 점진적 영상 전송)

  • 황찬식
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.5
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    • pp.685-694
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    • 1993
  • A progressive image transmission (PIT) scheme based on the classified transform vector quantization (CVQ) technique using the lapped orthogonal transform (LOT) and human visual system (HVS) weighting is proposed in this paper. Conventional block transform coding of images using DCT produces in general undesirable block-artifacts at low bit rates. In this paper, image blocks are transformed using the LOT and classified into four classes based on their structural properties and further divided adaptively into subvectors depending on the LOT coefficient statistics with HVS weighting to improve the reconstructed image quality by adaptive bit allocation. The subvectors are vector quantized and transmitted progressively. Coding tests using computer simulations show that the LOT/CVQ based PIT of images is a effective coding scheme. The results are also compared with those obtained using PIT/DCTVQ. The LOT/CVQ based PIT reduces the block-artifacts significantly.

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Markov Chain Model for Synthetic Generation by Classification of Daily Precipitaion Amount into Multi-State (강수계열의 상태분류에 의한 Markov 연쇄 모의발생모형)

  • Kim, Ju-Hwan;Park, Chan-Yeong
    • Water for future
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    • v.29 no.6
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    • pp.155-166
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    • 1996
  • A finite element model for simulating gradually and rapidly varied unsteady flow in open channel is developed based on dynamic wave equation using Petrov-Galerkin method. A matrix stability analysis shows the selective damping of short wave lengths and excellent phase accuracies achived by Petrov-Galerkin method. Whereas the Preissmann scheme displays less selective damping and poor phase accuracies, and Bubnov-Galerkin method shows nondissipative characteristics whicn causes a divergence problem in short wave length. The analysis also shows that the Petrov-Galerkin method displays the desirable combination of selective damping of high frequency progressive waves over a wide range of Courant number and good phase accuracy at low Courant number. Therefore, the Petrov-Galerkin can be effectively applied to gradually and rapidly varied unsteady flow.

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