• Title, Summary, Keyword: Multi-Resolution

Search Result 1,318, Processing Time 0.044 seconds

Characteristics of Multi-Spatial Resolution Satellite Images for the Extraction of Urban Environmental Information

  • Seo, Dong-Jo;Park, Chong-Hwa;Tateishi, Ryutaro
    • Proceedings of the KSRS Conference
    • /
    • /
    • pp.218-224
    • /
    • 1998
  • The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

  • PDF

Studies on the Operating Requirements of Multi-Resolution Modeling in Training War-Game Model and on the Solutions for Major Issues of Multi-Resolution Interoperation between Combat21 Model and TMPS (훈련용 워게임 모델의 다중해상도모델링 운영소요 및 전투21모델과 TMPS의 다중해상도 연동간 주요 이슈 해결 방안 연구)

  • Moon, Hoseok;Kim, Suhwan
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.21 no.6
    • /
    • pp.865-876
    • /
    • 2018
  • This study focuses on the operating requirements of multi-resolution modeling(MRM) in training war-game model and proposes solutions for major issues of multi-resolution interoperation between Combat21 model and tank multi-purpose simulator(TMPS). We study the operating requirements of MRM through interviews with defense M&S experts and literature surveys and report the various issues that could occur with low-resolution model Combat21 and high-resolution model TMPS linked, for example, when to switch objects, what information to exchange, what format to switch to, and how to match data resolutions. This study also addresses the purpose and concept of training using multi-resolution interoperation, role of each model included in multi-resolution interoperation, and issue of matching damage assessments when interoperated between models with different resolutions. This study will provide the common goals and directions of MRM research to MRM researchers, defense modeling & simulation organizations and practitioners.

Small Target Detection in Multi-Resolution Image Using Facet Model (다중 해상도 영상에서 페이싯 모델을 이용한 초소형 표적 검출)

  • Park, Ji-Hwan;Lee, Min-Woo;Lee, Chul-Hun;Joo, Jae-Heum;Nam, Ki-Gon
    • Journal of the Institute of Convergence Signal Processing
    • /
    • v.12 no.2
    • /
    • pp.76-82
    • /
    • 2011
  • In this paper, we propose the technique to detect the location and size of the small target in multi-resolution image using cubic facet model. The input image is reduced by the multi-resolution and we obtain the multi-resolution images. We apply the facet model and the local maxima conditions to the multi-resolution images of each level. And then, we detect the location of the small target. We estimate that the location at the maximum of the $D_2$ which means the local maxima value of the facet model in the multi-resolution images is the location of the small target. We can detect the small target of the various size about the multi-resolution images of each level. In this paper, we experimented in the various infrared images with the small target. The method using the typical facet model applies a mask. However, the proposed method applies a mask in the multi-resolution images. We verified to vary the mask size and differ the size of the small target. The proposed algorithm can detect the location and size of the small target.

A Study on Feature-Based Multi-Resolution Modelling - Part II: System Implementation and Criteria for Level of Detail (특징형상기반 다중해상도 모델링에 관한 연구 - Part II: 시스템 구현 및 상세수준 판단기준)

  • Lee K.Y.;Lee S.H.
    • Korean Journal of Computational Design and Engineering
    • /
    • v.10 no.6
    • /
    • pp.444-454
    • /
    • 2005
  • Recently, the requirements of multi-resolution models of a solid model, which represent an object at multiple levels of feature detail, are increasing for engineering tasks such as analysis, network-based collaborative design, and virtual prototyping and manufacturing. The research on this area has focused on several topics: topological frameworks for representing multi-resolution solid models, criteria for the level of detail (LOD), and generation of valid models after rearrangement of features. As a solution to the feature rearrangement problem, the new concept of the effective zone of a feature is introduced in the former part of the paper. In this paper, we propose a feature-based non-manifold modeling system to provide multi-resolution models of a feature-based solid or non-manifold model on the basis of the effective feature zones. To facilitate the implementation, we introduce the class of the multi-resolution feature whose attributes contain all necessary information to build a multi-resolution solid model and extract LOD models from it. In addition, two methods are introduced to accelerate the extraction of LOD models from the multi-resolution modeling database: the one is using an NMT model, known as a merged set, to represent multi-resolution models, and the other is storing differences between adjacent LOD models to accelerate the transition to the other LOD. We also suggest the volume of the feature, regardless of feature type, as a criterion for the LOD. This criterion can be used in a wide range of applications, since there is no distinction between additive and subtractive features unlike the previous method.

Mobile Robot navigation using an Multi-resolution Electrostatic Potential Filed

  • Kim, Cheol-Taek;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.690-693
    • /
    • 2004
  • This paper proposes a multi-resolution electrostatic potential field (MREPF) based solution to the mobile robot path planning and collision avoidance problem in 2D dynamic environment. The MREPF is an environment method in calculation time and updating field map. The large scale resolution map is added to EPF and this resolution map interacts with the small scale resolution map to find an optimal solution in real time. This approach can be interpreted with Atlantis model. The simulation studies show the efficiency of the proposed algorithm.

  • PDF

Multi- Resolution MSS Image Fusion

  • Ghassemian, Hassan;Amidian, Asghar
    • Proceedings of the KSRS Conference
    • /
    • /
    • pp.648-650
    • /
    • 2003
  • Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

  • PDF

COMPOUNDED METHOD FOR LAND COVERING CLASSIFICATION BASED ON MULTI-RESOLUTION SATELLITE DATA

  • HE WENJU;QIN HUA;SUN WEIDONG
    • Proceedings of the KSRS Conference
    • /
    • /
    • pp.116-119
    • /
    • 2005
  • As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

  • PDF

Content-Based Image Retrieval Using Combined Color and Texture Features Extracted by Multi-resolution Multi-direction Filtering

  • Bu, Hee-Hyung;Kim, Nam-Chul;Moon, Chae-Joo;Kim, Jong-Hwa
    • Journal of Information Processing Systems
    • /
    • v.13 no.3
    • /
    • pp.464-475
    • /
    • 2017
  • In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi-resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.

Information Acquisition of Simulation Objects by Resolution in Multi-resolution Model based War Game (다중 해상도 모델 기반 워게임 체계에서 해상도별 모의 객체의 정보 획득)

  • Bae, Hyun Shik;Rhee, Eun joo
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.22 no.1
    • /
    • pp.147-154
    • /
    • 2018
  • In this paper, we propose methods to acquire enemy object information, which is frequently required in multi-resolution model based war game and affects the simulation performance. In the information request method, a multi-resolution model selects information of a specific resolution and provides them to external objects. In the information announcement method, a multi-resolution model announces all information, and external objects select information of a specific resolution. In the information sharing method, external objects obtains information of a specific resolution by inquiring all information of a multi-resolution model which are stored in a shared space. Simulation results show that the information sharing method is more efficient than the information request method and the information announcement method because the information acquisition is fast. In addition, the proposed methods will increase the efficiency of war game operation by shortening the time for acquiring enemy forces' information.

Multi-resolution DenseNet based acoustic models for reverberant speech recognition (잔향 환경 음성인식을 위한 다중 해상도 DenseNet 기반 음향 모델)

  • Park, Sunchan;Jeong, Yongwon;Kim, Hyung Soon
    • Phonetics and Speech Sciences
    • /
    • v.10 no.1
    • /
    • pp.33-38
    • /
    • 2018
  • Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.