• Title/Summary/Keyword: matching property

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Multiple Candidate Matching Pursuit (다중 후보 매칭 퍼슛)

  • Kwon, Seokbeop;Shim, Byonghyo
    • Journal of Broadcast Engineering
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    • v.17 no.6
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    • pp.954-963
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    • 2012
  • As a greedy algorithm reconstructing the sparse signal from underdetermined system, orthogonal matching pursuit (OMP) algorithm has received much attention. In this paper, we multiple candidate matching pursuit (MuCaMP), which builds up candidate support set in every iteration and uses the minimum residual at last iteration. Using the restricted isometry property (RIP), we derive the sufficient condition for MuCaMP to recover the sparse signal exactly. The MuCaMP guarantees to reconstruct the K-sparse signal when the sensing matrix satisfies the RIP constant ${\delta}_{N+K}<\frac{\sqrt{N}}{\sqrt{K}+3\sqrt{N}}$. In addition, we show a recovery performance both noiseless and noisy measurements.

IKONOS Stereo Matching with Land Cover Map for DEM Generation

  • Lee, Hyo-Seong;Ahn, Ki-Weon;Park, Byung-Guk;Han, Dong-Yeob
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.580-583
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    • 2007
  • Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

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Fast Matching Pursuit Method Using Property of Symmetry and Classification for Scalable Video Coding

  • Oh, Soekbyeung;Jeon, Byeungwoo
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.278-281
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    • 2000
  • Matching pursuit algorithm is a signal expansion technique whose efficiency for motion compensated residual image has already been demonstrated in the MPEG-4 framework. However, one of the practical concerns related to applying matching pursuit algorithm to real-time scalable video coding is its massive computation required for finding dictionary elements. In this respective, this paper proposes a fast algorithm, which is composed of three sub-methods. The first method utilizes the property of symmetry in 1-D dictionary element and the second uses mathematical elimination of inner product calculation in advance, and the last one uses frequency property of 2-D dictionary. Experimental results show that our algorithm needs about 30% computational load compared to the conventional fast algorithm using separable property of 2-D gabor dictionary with negligible quality degradation.

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Efficient Time-Series Subsequence Matching Using MBR-Safe Property of Piecewise Aggregation Approximation (부분 집계 근사법의 MBR-안전 성질을 이용한 효율적인 시계열 서브시퀀스 매칭)

  • Moon, Yang-Sae
    • Journal of KIISE:Databases
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    • v.34 no.6
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    • pp.503-517
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    • 2007
  • In this paper we address the MBR-safe property of Piecewise Aggregation Approximation(PAA), and propose an of efficient subsequence matching method based on the MBR-safe PAA. A transformation is said to be MBR-safe if a low-dimensional MBR to which a high- dimensional MBR is transformed by the transformation contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. Using an MBR-safe transformation we can reduce the number of lower-dimensional transformations required in similar sequence matching, since it transforms a high-dimensional MBR itself to a low-dimensional MBR directly. Furthermore, PAA is known as an excellent lower-dimensional transformation single its computation is very simple, and its performance is superior to other transformations. Thus, to integrate these advantages of PAA and MBR-safeness, we first formally confirm the MBR-safe property of PAA, and then improve subsequence matching performance using the MBR-safe PAA. Contributions of the paper can be summarized as follows. First, we propose a PAA-based MBR-safe transformation, called mbrPAA, and formally prove the MBR-safeness of mbrPAA. Second, we propose an mbrPAA-based subsequence matching method, and formally prove its correctness of the proposed method. Third, we present the notion of entry reuse property, and by using the property, we propose an efficient method of constructing high-dimensional MBRs in subsequence matching. Fourth, we show the superiority of mbrPAA through extensive experiments. Experimental results show that, compared with the previous approach, our mbrPAA is 24.2 times faster in the low-dimensional MBR construction and improves subsequence matching performance by up to 65.9%.

A New Stereo Matching Algorithm based on Variable Windows using Frequency Information in DWT Domain (DWT 영역에서의 주파수 정보를 활용한 가변 윈도우 기반의 스테레오 정합 알고리즘)

  • Seo, Young-Ho;Koo, Ja-Myung;Kim, Dong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.7
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    • pp.1437-1446
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    • 2012
  • In this paper we propose a new stereo matching algorithm which is suitable for application to obtain depth information with high-speed in stereoscopic camera environment. For satisfying these condition we propose a new adaptive stereo matching technique using frequency information in discrete wavelet (DWT) domain and variable matching window. The size of the matching window is selected by analysis of the local property of the image in spatial domain and the feature and scaling factor of the matching window is selected by the frequency property in the frequency domain. For using frequency information we use local DWT and global DWT. We identified that the proposed technique has better peak noise to signal ratio (PSNR) than the fixed matching techniques with similar complexity.

Matching Size Determination According to Land Cover Property of IKONOS Stereo Imagery (IKONOS 입체영상의 토지피복 특성에 따른 정합영역 크기 결정)

  • Lee, Hyo-Seong;Park, Byung-Uk;Lee, Byung-Gil;Ahn, Ki-Weon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_2
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    • pp.587-597
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    • 2007
  • This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters to minimize search area, the matching is carried out based on this line. The experiment is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively.

Generalized Orthogonal Matching Pursuit (일반화된 직교 매칭 퍼슛 알고리듬)

  • Kwon, Seok-Beop;Shim, Byong-Hyo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.122-129
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    • 2012
  • As a greedy algorithm reconstructing the sparse signal from underdetermined system, orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we present an extension of OMP for pursuing efficiency of the index selection. Our approach, referred to as generalized OMP (gOMP), is literally a generalization of the OMP in the sense that multiple (N) columns are identified per step. Using the restricted isometry property (RIP), we derive the condition for gOMP to recover the sparse signal exactly. The gOMP guarantees to reconstruct sparse signal when the sensing matrix satisfies the RIP constant ${\delta}_{NK}$ < $\frac{\sqrt{N}}{\sqrt{K}+2\sqrt{N}}$. In addition, we show recovery performance and the reduced number of iteration required to recover the sparse signal.

Hierarchical hausdorff distance matching using pyramid structures (피라미드 구조를 이용한 계층적 hausdorff distance 정합)

  • 권오규;심동규;박래홍
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.12
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    • pp.70-80
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    • 1997
  • This paper proposes a hierarchical Hausdorff distance (HD) matching algorithm baased on coarse-to-fine approach. It reduces the computational complexity greatly by using the pyramidal structures consisting of distance transform (DT) and edge pyramids. Also, inthe proposed hierarchical HD matching, a thresholding method is presented to find an optimal matching position with small error, in which the threshold values are determined by using the property between adjacent level of a DT map pyramid. By computer simulation, the performance of the conventional and proposed hierarchical HD matching algorithms is compared in therms of the matching position for binary images containing uniform noise.

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Wavelet based Area Matching of Satellite Imagery

  • Park, J.H.;Park, J.H.;Kim, K.O.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.423-425
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    • 2003
  • In this paper, we propose a new scheme for matching specified areas in a satellite image, which is a very efficient method because it can be effectively applied to images that have various features. These features may include different spatial resolution and brightness; sometimes they may different geometrical property. The proposed method can be applied to some application fields such as mosaicing of satellite imagery, GCP matching.

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A Stereo Matching by the Iterative Relaxation Using the Consensus of Matching Possibility (정합 일치성을 이용한 반복 이완 스테레오 정합)

  • 이왕국;김용석;도경훈;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.1
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    • pp.39-49
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    • 1995
  • Stereo vision is useful to obtain three dimensional depth information from two images taken from different view points. In this paper, we reduce searching area for correspondence by using the intra-scanline constraint, and utilize the inter-scanline constraint and the property of disparity continuity among the neighboring pixels for relaxation. Nodes with 3-D stucture are located on the axes of two views, and have matching possibility of correspondent pixels of two images. A matching is accepted if a node at the intersection of the disparity axes has the greatest matching possibility. Otherwise, the matching possibility of the node is updated by relaxation with the cooperation of neighboring nodes. Further relaxation with competition of two views is applied to a matching possibility of randomly selected node. The consensus of two views increases the confidence of matching, and removes a blurring phenomenon on the discontinuity of object. This approach has been tested with various types of image such as random dot stereogram and aerial image, and the experimental results show good matching performance.

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