• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.180-183
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• 2002

In this paper, we propose new unsharp masking technique based on the multiscale gradient planes. The unsharp masking technique is implemented as a high-pass filter and improves the sharpness of degraded images. However, the conventional unsharp masking enhances the noise component simultaneously. To reduce the noise influence, we introduce the edge information from the difference of the gradient values between two consecutive scales of the multiscale gradient. The multiscale gradient indicates the presence of image edges as the ratio between the gradients between two different scales by its multiscale nature. The noise reduction of the proposed method does not depend on the variance of images and noises. In experiment, we demonstrate enhancement results for blurred noisy images and compare with the conventional cubic unsharp masking technique.

• Earthquakes and Structures
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• v.12 no.6
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• pp.673-687
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• 2017

A three-dimensional; structural health monitoring; vertical; planar; cross-sample entropy; multiscaleA three-dimensional structural health monitoring (SHM) system based on multiscale entropy (MSE) and multiscale cross-sample entropy (MSCE) is proposed in this paper. The damage condition of a structure is rapidly screened through MSE analysis by measuring the ambient vibration signal on the roof of the structure. Subsequently, the vertical damage location is evaluated by analyzing individual signals on different floors through vertical MSCE analysis. The results are quantified using the vertical damage index (DI). Planar MSCE analysis is applied to detect the damage orientation of damaged floors by analyzing the biaxial signals in four directions on each damaged floor. The results are physically quantified using the planar DI. With progressive vertical and planar analysis methods, the damaged floors and damage locations can be accurately and efficiently diagnosed. To demonstrate the performance of the proposed system, performance evaluation was conducted on a three-dimensional seven-story steel structure. According to the results, the damage condition and elevation were reliably detected. Moreover, the damage location was efficiently quantified by the DI. Average accuracy rates of 93% (vertical) and 91% (planar) were achieved through the proposed DI method. A reference measurement of the current stage can initially launch the SHM system; therefore, structural damage can be reliably detected after major earthquakes.

• Interaction and multiscale mechanics
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• v.2 no.2
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• pp.109-128
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• 2009

Multiscale analysis is a stepwise procedure to obtain macro-scale material laws, directly amenable to structural analysis, based on information from finer scales. An essential ingredient of this mode of analysis is mathematical homogenization of heterogeneous materials at these scales. The purpose of this paper is to demonstrate the potential of multiscale analysis in civil engineering. The materials considered in this work are wood, shotcrete, and asphalt.

• Journal of the Korean earth science society
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• v.25 no.2
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• pp.109-114
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• 2004

A wavelet method is applied to the analysis of gravity potential. One scaling function is proposed to generate wavelet. The scaling function is shown to be replaced to the Green’s function in gravity potential. The upward continuation can be expressed as a wavelet transform i.e. convolution with the scaling function. The scaling factor indicates the height variation. The multiscale edge detection is carried by connecting the local maxima of the wavelet transform at scales. The multiscale edge represents discontinuity of the geological structure. The multiscale edge method is applied to gravity data from Masan and Changwon.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1046-1057
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• 2004

An image enhancement method using both homomorphic transformation and multiscale decomposition is proposed. The original image is first transformed to homomorphic domain by taking the logarithm, is then separated to multiscales. These multiscales are combined with weighting. The combined signal is exponentially transformed back into intensity domain. In homomorphic domain, the magnitude control of low frequency component make change the dynamic range, and the magnitude control of the other frequency components contribute to enhancement of the contrast. The "${\AA}$ trous" algorithm, which has a simple and efficient scheme, is used for multiscale decomposition. The performance of proposed method is verified by simulation.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.403-415
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• 2018

In the present study, nonlinear dynamic response of polymer-CNT-fiber multiscale nanocomposite plate resting on elastic foundations in thermal environments using the finite element method is performed. In this regard, the governing equations are derived based on Inverse Hyperbolic Shear Deformation Theory and von $K{\acute{a}}rm{\acute{a}}n$ geometrical nonlinearity. Three type of distribution of temperature through the thickness of the plate namely, uniform linear and nonlinear are considered. The considered element is C1-continuous with 15 DOF at each node. The effective material properties of the multiscale composite are calculated using Halpin-Tsai equations and fiber micromechanics in hierarchy. The carbon nanotubes are assumed to be uniformly distributed and randomly oriented through the epoxy resin matrix. Five types of impulsive loads are considered, namely the step, sudden, triangular, half-sine and exponential pulses. After examining the validity of the present work, the effects of the weight percentage of SWCNTs and MWCNTs, nanotube aspect ratio, volume fraction of fibers, plate aspect, temperature, elastic foundation parameters, distribution of temperature and shape of impulsive load on nonlinear dynamic response of CNT reinforced multi-phase laminated composite plate are studied in details.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1851-1863
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• 2015

– In the paper, to handle the problem of traditional bag-of-features model ignoring the spatial relationship of local features in human action recognition, we proposed a Multiscale Spatial Position Coding under Locality Constraint method. Specifically, to describe this spatial relationship, we proposed a mixed feature combining motion feature and multi-spatial-scale configuration. To utilize temporal information between features, sub spatial-temporal-volumes are built. Next, the pooled features of sub-STVs are obtained via max-pooling method. In classification stage, the Locality-Constrained Group Sparse Representation is adopted to utilize the intrinsic group information of the sub-STV features. The experimental results on the KTH, Weizmann, and UCF sports datasets show that our action recognition system outperforms the classical local ST feature-based recognition systems published recently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.544-564
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• 2022

Underwater images often suffer from color distortion, blurring and low contrast, which is caused by the propagation of light in the underwater environment being affected by the two processes: absorption and scattering. To cope with the poor quality of underwater images, this paper proposes a multiscale fusion underwater image enhancement method based on channel attention mechanism and local binary pattern (LBP). The network consists of three modules: feature aggregation, image reconstruction and LBP enhancement. The feature aggregation module aggregates feature information at different scales of the image, and the image reconstruction module restores the output features to high-quality underwater images. The network also introduces channel attention mechanism to make the network pay more attention to the channels containing important information. The detail information is protected by real-time superposition with feature information. Experimental results demonstrate that the method in this paper produces results with correct colors and complete details, and outperforms existing methods in quantitative metrics.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.589-592
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• 1999

Matching is a key problem in computer vision, image analysis and pattern recognition. In this paper a multiscale image matching algorithm by wavelet local extrema is proposed. This algorithm is based on the multiscale wavelet transform of the curvature which can utilize both the information of local extrema positions and magnitudes of transform results. This method has advantages in computational cost to a single scale image matching. It is also rotation-, translation-, and scale-independent image matching method. This matching can be used for the recognition of occluded objects.

• Korean Journal of Mathematics
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• v.13 no.2
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• pp.127-137
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• 2005

The objective of numerical analysis is to devise and analyze efficient algorithms or numerical methods for equations arising in mathematical modeling for science and engineering. In this article, we present some recent topics in computational mathematics, specially in the finite element method and overview the development of the mixed finite element method in the context of second order elliptic and parabolic problems. Multiscale methods such as MsFEM, HMM, and VMsM are included.