• Title/Summary/Keyword: Cover-image

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Standardizing Agriculture-related Land Cover Classification Scheme Using IKONOS Satellite Imagery (IKONOS 영상자료를 이용한 농업관련 토지피복 분류기준 설정 연구)

  • 홍성민;정인균;김성준
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.261-265
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    • 2004
  • The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat+ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

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Comparative Analysis of Fashion Characteristics on the Cover of Domestic Licensed Fashion Magazines - Focused on ELLE, VOGUE, W - (국내 라이선스 패션잡지 표지에 나타난 패션특성의 비교분석 - ELLE, VOGUE, W를 중심으로 -)

  • Lee, Hyunji;Lee, Kyunghee
    • Fashion & Textile Research Journal
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    • v.21 no.1
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    • pp.1-12
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    • 2019
  • The purpose of this study is to examine the fashion characteristics of fashion magazine cover by comparing and analyzing the formative characteristics of fashion, visual design characteristics and illustration vocabulary on the cover of 3 fashion magazines. The data analysis criteria consisted of the formative elements of fashion (fashion design element, fashion coordination element) and visual design element (color, illustration lexical layout, model photograph type). Data analysis methods were statistical analysis, stepwise lexical analysis, and content analysis. The results of the study are as follows. First, the formative characteristics of fashion on the cover of fashion magazines show that ELLE is a feminine and elegant characteristics, VOGUE is a modern, chic and mannish characteristics, and W is avant-garde and neutral characteristics. Second, visual design characteristics on the cover of fashion magazines, ELLE and VOGUE use modern and simple modern sensibility by using monotonous background color and background color number, and W showed original image characteristic by using various colors. Third, as a result of the illustration lexical analysis on the cover of fashion magazines, 4 core keywords of trend, star, event, and life appeared in 3 magazines in common. Elle differentiates by innovation, Vogue by discrimination, W by reconstruction.

Performance Evaluation of Snow Detection Using Himawari-8 AHI Data (Himawari-8 AHI 적설 탐지의 성능 평가)

  • Jin, Donghyun;Lee, Kyeong-sang;Seo, Minji;Choi, Sungwon;Seong, Noh-hun;Lee, Eunkyung;Han, Hyeon-gyeong;Han, Kyung-soo
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.1025-1032
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    • 2018
  • Snow Cover is a form of precipitation that is defined by snow on the surface and is the single largest component of the cryosphere that plays an important role in maintaining the energy balance between the earth's surface and the atmosphere. It affects the regulation of the Earth's surface temperature. However, since snow cover is mainly distributed in area where human access is difficult, snow cover detection using satellites is actively performed, and snow cover detection in forest area is an important process as well as distinguishing between cloud and snow. In this study, we applied the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to the geostationary satellites for the snow detection of forest area in existing polar orbit satellites. On the rest of the forest area, the snow cover detection using $R_{1.61{\mu}m}$ anomaly technique and NDSI was performed. As a result of the indirect validation using the snow cover data and the Visible Infrared Imaging Radiometer (VIIRS) snow cover data, the probability of detection (POD) was 99.95 % and the False Alarm Ratio (FAR) was 16.63 %. We also performed qualitative validation using the Himawari-8 Advanced Himawari Imager (AHI) RGB image. The result showed that the areas detected by the VIIRS Snow Cover miss pixel are mixed with the area detected by the research false pixel.

Analysis on Topographic Normalization Methods for 2019 Gangneung-East Sea Wildfire Area Using PlanetScope Imagery (2019 강릉-동해 산불 피해 지역에 대한 PlanetScope 영상을 이용한 지형 정규화 기법 분석)

  • Chung, Minkyung;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.36 no.2_1
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    • pp.179-197
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    • 2020
  • Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.

Enhancement of Classification Accuracy and Environmental Information Extraction Ability for KOMPSAT-1 EOC using Image Fusion (영상합성을 통한 KOMPSAT-1 EOC의 분류정확도 및 환경정보 추출능력 향상)

  • Ha, Sung Ryong;Park, Dae Hee;Park, Sang Young
    • Journal of the Korean Association of Geographic Information Studies
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    • v.5 no.2
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    • pp.16-24
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    • 2002
  • Classification of the land cover characteristics is a major application of remote sensing. The goal of this study is to propose an optimal classification process for electro-optical camera(EOC) of Korea Multi-Purpose Satellite(KOMPSAT). The study was carried out on Landsat TM, high spectral resolution image and KOMPSAT EOC, high spatial resolution image of Miho river basin, Korea. The study was conducted in two stages: one was image fusion of TM and EOC to gain high spectral and spatial resolution image, the other was land cover classification on fused image. Four fusion techniques were applied and compared for its topographic interpretation such as IHS, HPF, CN and wavelet transform. The fused images were classified by radial basis function neural network(RBF-NN) and artificial neural network(ANN) classification model. The proposed RBF-NN was validated for the study area and the optimal model structure and parameter were respectively identified for different input band combinations. The results of the study propose an optimal classification process of KOMPSAT EOC to improve the thematic mapping and extraction of environmental information.

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Image Watermarking Scheme Based on Scale-Invariant Feature Transform

  • Lyu, Wan-Li;Chang, Chin-Chen;Nguyen, Thai-Son;Lin, Chia-Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.10
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    • pp.3591-3606
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    • 2014
  • In this paper, a robust watermarking scheme is proposed that uses the scale-invariant feature transform (SIFT) algorithm in the discrete wavelet transform (DWT) domain. First, the SIFT feature areas are extracted from the original image. Then, one level DWT is applied on the selected SIFT feature areas. The watermark is embedded by modifying the fractional portion of the horizontal or vertical, high-frequency DWT coefficients. In the watermark extracting phase, the embedded watermark can be directly extracted from the watermarked image without requiring the original cover image. The experimental results showed that the proposed scheme obtains the robustness to both signal processing and geometric attacks. Also, the proposed scheme is superior to some previous schemes in terms of watermark robustness and the visual quality of the watermarked image.

Image Fusion for Improving Classification

  • Lee, Dong-Cheon;Kim, Jeong-Woo;Kwon, Jay-Hyoun;Kim, Chung;Park, Ki-Surk
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1464-1466
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    • 2003
  • classification of the satellite images provides information about land cover and/or land use. Quality of the classification result depends mainly on the spatial and spectral resolutions of the images. In this study, image fusion in terms of resolution merging, and band integration with multi-source of the satellite images; Landsat ETM+ and Ikonos were carried out to improve classification. Resolution merging and band integration could generate imagery of high resolution with more spectral bands. Precise image co-registration is required to remove geometric distortion between different sources of images. Combination of unsupervised and supervised classification of the fused imagery was implemented to improve classification. 3D display of the results was possible by combining DEM with the classification result so that interpretability could be improved.

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Data Hiding in Halftone Images by XOR Block-Wise Operation with Difference Minimization

  • Yang, Ching-Nung;Ye, Guo-Cin;Kim, Cheon-Shik
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.2
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    • pp.457-476
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    • 2011
  • This paper presents an improved XOR-based Data Hiding Scheme (XDHS) to hide a halftone image in more than two halftone stego images. The hamming weight and hamming distance is a very important parameter affecting the quality of a halftone image. For this reason, we proposed a method that involves minimizing the hamming weights and hamming distances between the stego image and cover image in $2{\times}2$-pixel grids. Moreover, our XDHS adopts a block-wise operation to improve the quality of a halftone image and stego images. Furthermore, our scheme improves security by using a block-wise operation with A-patterns and B-patterns. Our XDHS method achieves a high quality with good security compared to the prior arts. An experiment verified the superiority of our XDHS compared with previous methods.

UAV-based Land Cover Mapping Technique for Monitoring Coastal Sand Dunes

  • Choi, Seok Keun;Kim, Gu Hyeok;Choi, Jae Wan;Lee, Soung Ki;Choi, Do Yoen;Jung, Sung Heuk;Chun, Sook Jin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.1
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    • pp.11-22
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    • 2017
  • In recent years, coastal dune erosion has accelerated as various structures have been developed around the coastal dunes. A land cover map should be developed to identify the characteristics of sand dunes and to monitor the condition of sand dunes. The Korean Ministry of Environment's land cover maps suffer from problems, such as limited classes, target areas, and durations. Thus, this study conducted experiments using RGB and multispectral images based on UAV (Unmanned Aerial Vehicle) over an approximately one-year cycle to create a land cover map of coastal dunes. RF (Random Forest) classifier was used for the analysis in accordance with the experimental region's characteristics. The pixel- and object-based classification results obtained by using RGB and multispectral cameras were evaluated, respectively. The study results showed that object-based classification using multispectral images had the highest accuracy. Our results suggest that constant monitoring of coastal dunes can be performed effectively.

UN-Substituted Video Steganography

  • Maria, Khulood Abu;Alia, Mohammad A.;Alsarayreh, Maher A.;Maria, Eman Abu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.1
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    • pp.382-403
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    • 2020
  • Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.