• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.633-644
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• 2004

In this paper, we notice that the original NTSS algorithm can be proposed as the NTSS-3 Level algorithm by the multi-resolution technique. The fast block matching algorithm affects the speed by the patten combination and this paper proposes the block matching algorithm in different levels by multi-resolution technique, quite different from the original NTSS Patten. The block matching algorithm requires the multi-candidate to reduce the occurrence of low-image quality by the local minima problem. The simulation result compared to FS shows search speed 16 times quicker, and the PSNR 0.11-0.12［dB］ gets improved Image quality compared to the original fast block matching algorithm NTSS, and the speed is improved up to 0.1 times for improved image by the search point portion.

• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.549-557
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• 2005

The requirements of multi-resolution models of feature-based solids, which represent an object at many levels of feature detail, are increasing for engineering purposes, such as analysis, network-based collaborative design, virtual prototyping and manufacturing. To provide multi-resolution models for various applications, it is essential to generate adequate solid models at varying levels of detail (LOD) after feature rearrangement, based on the LOD criteria. However, the non-commutative property of the union and subtraction Boolean operations is a severe obstacle to arbitrary feature rearrangement. To solve this problem we propose history-based Boolean operations that satisfy the commutative law between union and subtraction operations by considering the history of the Boolean operations. Because these operations guarantee the same resulting shape as the original and reasonable shapes at the intermediate LODs for an arbitrary rearrangement of its features, various LOD criteria can be applied for multi-resolution modeling in different applications.

• Computers and Concrete
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• v.20 no.5
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.131-139
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• 2007

This paper proposed a multi-resolution algorithm. Its search point and complexity were compared with those of block match algorithm. Also the speed up comparison was made with the block match algorithm. The proposed multi-resolution NTSS-3 Level algorithm was compared again with its targets, TSS-3 Level algorithm and NTSS algorithm. The comparison results showed that the NTSS-3 Level algorithm was superior in search point and speed up. Accordingly, the proposed NTSS-3 Level algorithm was two to three times better in search point and two to four times better in complexity calculation than those of the compared object, the block match algorithm. In speed up, the proposed NTSS-3 Level algorithm was two times better. Accordingly, the proposed multi-resolution NTSS-3 Level algorithm showed PSNR ration portion excellency in search point and speed up.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.899-905
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• 2003

An intermediate images generation method using multi-resolution based hierarchical block matching disparity map is proposed. This method is composed of a disparity estimation, an occlusion detection and intermediate image synthesis. For the disparity estimation, which is one of the important processes in intermediate image synthesis, we use the multi-resolution based hierarchical block matching algorithm to overcome the imperfect ness of block matching algorithm. The proposed method makes disparity maps more accurate and dense by multi-resolution based hierarchical block matching, and the estimated disparity maps are used to generate intermediate images of stereo images. Generated intermediate images show 0.1∼1.4 ㏈ higher PSNR than the images obtained by block matching algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.828-831
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• 2005

In feature-based multi-resolution modeling, the features are rearranged according to a criterion for the levels of detail (LOD) of multi-resolution models. In this paper, two different LOD criteria are investigated and discussed. The one is the volumes of subtractive features, together with the precedence of additive features over subtractive features. The other is the volumes of features, regardless of whether the feature types are subtractive or additive. In addition, the algorithms to define and extract the LOD models based on the criteria are also described. The criterion of the volumes of features can be used for a wide range of applications in CAD and CAE in virtue of its generality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.67-73
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• 2008

In the Markov network which models disparity map with the Markov Random Field(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixels. Belief propagation algorithm required much iteration for accurate result. In this paper, we propose the stereo matching algorithm using belief propagation in multi-resolution domain. Multi-resolution method based on wavelet or lifting can reduce the search area, therefore this algorithm can generate disparity map with fast speed.

• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.558-566
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• 2005

We propose a feature-based multi-resolution representation of B-rep solid models using history-based Boolean operations based on the merge-and-select algorithm. Because union and subtraction are commutative in the history-based Boolean operations, the integrity of the models at various levels of detail (LOD) is guaranteed for the reordered features regardless of whether the features are subtractive or additive. The multi-resolution solid representation proposed in this paper includes a non-manifold topological merged-set model of all feature primitives as well as a feature-modeling tree reordered consistently with a given LOD criterion. As a result, a B-rep solid model for a given LOD can be provided quickly, because the boundary of the model is evaluated without any geometric calculation and extracted from the merged set by selecting the entities contributing to the LOD model shape.

• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.339-346
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• 2003

This paper provides a framework for information assurance within collaborative design, based on a technique we call role-based viewing. Such role-based viewing is achieved through integration of multi-resolution geometry and security models. 3D models are geometrically partitioned, and the partitioning is used to create multi-resolution mesh hierarchies. Extracting a model suitable for access rights for individual designers within a collaborative design environment Is driven by an elaborate access control mechanism.