• 한국경영과학회지
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• 제42권3호
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• pp.1-12
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• 2017

In this paper, we generalize lifted inequalities to a 0-1 mixed-integer bilinear covering set with linear terms. This work is motivated by the observation that Generalized Bilinear Inequality (GBI) occurs in the Branch and Bound process. We find some conditions and prove the subadditivity of lifting functions for lifting to be sequence-independent. Using the theoretical results, we develop facet-defining inequalities for a GBI-defined set through three steps of lifting.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1015-1018
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• 2002

We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed onto a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures, We present a self-contained derivations, building the decomposition from the basic principles such as the Euclidean algorithm, with a focus on a applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the bi-orthogonal, i.e, non-unitary case. Lifting leads to a speed-up when compared to the standard implementation. We show that this lifting scheme can be applied in image compression efficiently

• IEIE Transactions on Smart Processing and Computing
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• 제2권1호
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• pp.1-10
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• 2013

In JPEG2000, the Cohen-Daubechies-Feauveau (CDF) 9/7-tap wavelet filter is implemented using the conventional lifting scheme. On the other hand, this wavelet filter has two problems: the filter coefficients remain complex, and the conventional lifting scheme does not consider the image edges in the coding process. This paper proposes an effective lifting scheme to solve these problems. For this purpose, optimal 9/7-tap wavelet filters were designed in two steps. In the first step, the appropriate filter coefficients were selected. In the second step, a median operator was employed to consider the image edges. The experimental results with the median lifting scheme and the combination of filter optimization with the median lifting show that the proposed methods outperform the well-known CDF 9/7-tap wavelet filter of JPEG2000 on the edge-dominant images.

• 한국산학기술학회논문지
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• 제4권3호
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• pp.263-269
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• 2003

이 논문은 3차원 정수 웨이브릿 변환을 이용한 손실 의료 영상 압축에 대한 방법을 보여준다. 의료영상에 3차원 웨이브릿 분할법과 3차원 spatial dependence tree를 이용한 Set Partitioning in Hierarchical Trees(SPIHT) algorithm을 제공한다. 또한 3차원 웨이브릿 분할법에서 정수 웨이브릿 필터들을 이용한 lifting방법을 이용하고, unitary 변환을 만들기 위하여 정확한 scaling을 이용한다. 압축률이 증가하면 할수록 인접한 coding unit사이에선 boundary effect가 생긴다. Video와 같지 않아서 인접한 coding unit사이에서의 boundary artifact는 보여서는 안 된다. 이러한 현상을 제거하기 위해서 인접한 coding unit사이에 axial domain으로 overlapping방법을 사용한다. 또한 코딩 할 때 여러 종류의 정수 필터들을 사용한다. 결과로 어떤 특정한 필터를 사용할 때 좋은 결과를 얻었고 overlapping방법을 사용했기 때문에 ringing artifacts는 거의 찾아 볼 수가 없게 되었다. 그리고 어두운 면을 코딩 할 때도 좋은 결과를 얻었다.

• 한국건설관리학회논문집
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• 제13권3호
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• pp.34-42
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• 2012

국내 공동주택의 리모델링 수월성 및 이에 따른 장수명화를 위해 그린 프레임 공법이 개발되었다. 그린 프레임 공법은 합성 프리캐스트 콘크리트 부재를 이용한 라멘구조로 벽식 구조와는 달리 양중 및 설치가 골조공사의 주공정으로 작용한다. 따라서 그린 프레임에 의한 적정 골조공사 공기 산정을 위해서는 체계적인 양중계획이 필요하다. 그러나 양중계획은 그린 프레임을 구성하는 요소인 합성 PC 부재(기둥, 보)의 단위 양중공정에 대한 분석이 선행되어야 한다. 따라서 본 연구는 그린 프레임 합성 PC 부재의 양중공정을 분석하는 것을 목적으로 한다. 이를 위해 합성 PC 기둥과 보의 양중절차와 시간을 도출하고, 그 결과를 사례 프로젝트에 적용하여 기준층의 양중 사이클을 분석한다. 본 연구의 결과는 향후 그린 프레임에 의한 골조공사 양중계획 시 핵심자료로 사용된다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2395-2398
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• 2003

This paper focuses on lossless medical image compression methods for medical images that operate on two-dimensional(2D) reversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm [1][3][9] to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and sometimes better in lossless coding than previous coding systems using 2D integer wavelet transforms on medical images.

• 대한조선학회논문집
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• 제57권2호
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• pp.114-123
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• 2020

A high-order potential-based panel method based on Green's theorem, with piecewise-linear dipole strength on triangular panels, is formulated for the analysis of potential flow around a three-dimensional wing. Previous low-order panel methods adopt square panels with piecewise-constant dipole strength, which results in inherent errors. Square panels can not represent a high curvature lifting body, such as propellers, since the four vertices of the square panel do not locate at the same flat plane. Moreover the piecewise-constant dipole strength induces inevitable errors due to the steps in dipole strength between adjacent panels. In this paper a high-order panel method is formulated to improve accuracy by adopting a piecewise linear dipole strength on triangular panels. Firstly, the square panels are replaced by triangular panels in order to increase the geometric accuracy in representing the shape of the object with large curvature. Next, the step difference of the dipole strength between adjacent panels is removed by adopting piecewise-linear dipole strength on the triangular panels. The calculated results by the present method is compared with analytical ones for simple non-lifting geometries, such as ellipsoid. The results for an elliptic wing with zero thickness at finite angle of attack are compared with Jordan's results. The comparison shows reasonable agrements for the both lifting and non-lifting bodies.

• 대한원격탐사학회지
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• 제22권1호
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• 한국인터넷방송통신학회논문지
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• 제9권1호
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• pp.1-9
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• 2009

본 논문에서는 리프팅 웨이브렛 변환을 이용한 디지털 영상의 워터마크 기술을 제안하였다. 이 워터마크 기술은 쉽게 비디오와 관련된 콘텐트에 대한 워터마크 기술로 확장 될 수 있다. 그래서 깊이 정보를 포함하는 다시점 영상을 효과적으로 압축할 수 있는 계층적 깊이 영상 구조라는 새로운 콘텐트에 제안 기술을 적용하였다. 이 방법은 기준 시점 영상에만 워터마크를 삽입하므로 그 과정이 간단하다는 장점을 가진다. 그리고 계층적 깊이 영상 구조의 특성상 나머지 시점 영상으로 워터마크가 전파되므로 모든 시점 영상에 대하여 저작권을 보호할 수 있다는 장점도 가지고 있다.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.256-266
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• 2021

The Convolutional Neural Network (CNN) has recently made potential improvements in face verification applications. In fact, different models based on the CNN have attained commendable progress in the classification rate using a massive amount of data in an uncontrolled environment. However, the enormous computation costs and the considerable use of storage causes a noticeable problem during training. To address these challenges, we focus on relevant data trained within the CNN model by integrating a lifting method for a better tradeoff between the data size and the computational efficiency. Our approach is characterized by the advantage that it does not need any additional space to store the features. Indeed, it makes the model much faster during the training and classification steps. The experimental results on Labeled Faces in the Wild and YouTube Faces datasets confirm that the proposed CNN framework improves performance in terms of precision. Obviously, our model deliberately designs to achieve significant speedup and reduce computational complexity in deep CNNs without any accuracy loss. Compared to the existing architectures, the proposed model achieves competitive results in face recognition tasks