221 research outputs found
High Quality Image Interpolation via Local Autoregressive and Nonlocal 3-D Sparse Regularization
In this paper, we propose a novel image interpolation algorithm, which is
formulated via combining both the local autoregressive (AR) model and the
nonlocal adaptive 3-D sparse model as regularized constraints under the
regularization framework. Estimating the high-resolution image by the local AR
regularization is different from these conventional AR models, which weighted
calculates the interpolation coefficients without considering the rough
structural similarity between the low-resolution (LR) and high-resolution (HR)
images. Then the nonlocal adaptive 3-D sparse model is formulated to regularize
the interpolated HR image, which provides a way to modify these pixels with the
problem of numerical stability caused by AR model. In addition, a new
Split-Bregman based iterative algorithm is developed to solve the above
optimization problem iteratively. Experiment results demonstrate that the
proposed algorithm achieves significant performance improvements over the
traditional algorithms in terms of both objective quality and visual perceptionComment: 4 pages, 5 figures, 2 tables, to be published at IEEE Visual
Communications and Image Processing (VCIP) 201
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Estimation of Gaussian process regression model using probability distance measures
A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification
approaches
Decline of Local Industrial Clusters in Japan and the Role of Merchant Coordinators for Sustainable Development of These Clusters
This study describes the present situation of the Chemical Shoes industrial cluster in Kobe city to empirically clarify issues related to Japanese industrial clusters. It reviews the extant literature on linkage firms and focuses on the crucial role that they play in the sustainability of industrial clusters. Additionally, a new rationale for the sustainability of industrial clusters is provided, and "merchant coordinators" are described as the new leading actors in the sustainability of industrial clusters by applying commercial theory, value network theory, and the latest network theory of community capital. Furthermore, the rationale for transcending beyond geographical constraints and the hidden cause for the difficulties faced by industrial clusters in being sustainable are explained. Finally, a hypothetical process model for the sustainability of industrial clusters is proposed by focusing on linkage firms and merchant coordinators.This paper is supported in part by a Grant-in-aid (KAKENHI) from Japan Society for the Promotion of Science (Project Number : 18H009090 & 18K018771)
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