• Title/Summary/Keyword: Cover-image

Search Result 715, Processing Time 0.028 seconds

Steganographic Method on Spatial Domain Using Modular Characteristic (모듈러 특성을 이용한 공간영역 기반의 심층암호)

  • Park Young-Ran;Shin Sang-Uk
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.16 no.2
    • /
    • pp.113-119
    • /
    • 2006
  • Image steganography is a secret communication method used to transmit secret messages that have been embedded into an image. To accommodate a secret message in a digital image, the original cover image is modified by the embedding algorithm. As a result, a stego image is obtained. The sender hides the secret message in a cover image that has no meaning, and then transmits the stego image to the receiver. In this paper, we propose a steganographic method based on spatial domain to embed a secret message using a difference value of two consecutive pixels and a secret quantization range. Especially, we use the modular operation for increasing of insertion information. Through experiments, we have shown that the proposed method has much mon payload capacity, average 60 percent, than some existing methods by using modular operation.

Accuracy evaluation of domestic and foreign land cover spectral libraries using hyperspectral image (초분광 영상을 활용한 국내외 토지피복 분광 라이브러리 정확도 평가)

  • Park, Geun Ryeol;Lee, Geun-Sang;Cho, Gi-Sung
    • Journal of Cadastre & Land InformatiX
    • /
    • v.51 no.2
    • /
    • pp.169-184
    • /
    • 2021
  • Recently, land cover spectral libraries have been widely used in studies to classify land cover based on hyperspectral images. Overseas, various institutions have built and provided land cover spectral libraries, but in Korea, the building and provision of land cover spectral libraries is insufficient. Against this background, the purpose of this study is to suggest the possibility of using domestic and foreign spectral libraries in the classification studies of domestic land cover. Band matching is required for comparative analysis of the spectral libraries and land cover classification using the spectral libraries, and in this study, an automation logic to automatically perform this is presented. In addition, the directly constructed domestic land cover spectral library and the existing overseas land cover spectral library were comparatively analyzed. As a result, the directly constructed land cover spectral library had the highest correlation coefficient of 0.974. Finally, for the accuracy evaluation, aerial hyperspectral images of the study area were supervised and classified using the domestic and foreign land cover spectral libraries using the SAM technique. As a result of the accuracy evaluation, it is judged that Soils, Artificial Materials, and Coatings among the classification items of the foreign land cover spectral library can be sufficiently applied to classify the cover in Korea.

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
    • /
    • v.25 no.6_2
    • /
    • pp.587-597
    • /
    • 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.

Estimation of Nonpoint Source Pollutant Loads of Juam-Dam Basin Based on the Classification of Satellite Imagery (위성영상 분류 기반 주암댐 유역 비점오염부하량 평가)

  • Lee, Geun-Sang;Kim, Tae-Keun
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.15 no.3
    • /
    • pp.1-12
    • /
    • 2012
  • The agricultural area was classified into dry and paddy fields in this study using the near-infrared band of Landsat TM to extract land cover classes that need to the application of Expected Mean Concentration (EMC) in nonpoint source works. The accuracy of image classification of the land cover map from Landsat TM image showed 83.61% and 78.41% respectively by comparing with the large and middle scale land cover map of Ministry of Environment. As the result of Soil Conservation Service (SCS) Curve Number (CN) using the land cover map from image classification, Dongbok dam and Dongbok stream basin were analyzed high. Also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of EMC of BOD, TN, TP by basin. And also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of non-point source through coupling with direct runoff. Therefore these basins were selected with the main area for the management of nonpoint source.

Tracking Changes of Snow Area Using Satellite Images of Mt.Halla at an Altitude of 1,600 m (위성화상을 이용한 고도 1,600 m 이상의 한라산 적설 면적 변화 추적)

  • Han, Gyung Deok;Yoon, Seong Uk;Chung, Yong Suk;Ahn, Jinhyun;Lee, Seung-Jae;Kim, Yoon Seok;Min, Taesun
    • Journal of Environmental Science International
    • /
    • v.31 no.10
    • /
    • pp.815-824
    • /
    • 2022
  • It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

Web-based synthetic-aperture radar data management system and land cover classification

  • Dalwon Jang;Jaewon Lee;Jong-Seol Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.7
    • /
    • pp.1858-1872
    • /
    • 2023
  • With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.

A study of Land-Cover Classification technique Using Fuzzy C-Mean Algorithm (Fuzzy C-Mean 알고리즘을 이용한 토지피복분류기법 연구)

  • 신석효;안기원;이주원;김상철
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
    • /
    • 2004.04a
    • /
    • pp.267-273
    • /
    • 2004
  • The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study is used to the high-resolution (6.6m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data(36 bands).We accomplished FCM classification technique with MLC technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method.

  • PDF

MONITORING OF LAND-COVER MOISTURE USING MULTITEMPORAL SAR IMAGES

  • Yoon, Bo-Yeol;Lee, Kwang-Jae;Kim, Youn-Soo;Kim, Yong-Seung
    • Proceedings of the KSRS Conference
    • /
    • v.2
    • /
    • pp.888-891
    • /
    • 2006
  • SAR image is not dependent on the weather condition and Sun's electromagnetic energy. But geometric distortions exist in almost all radar image, it need to be correction. The Radarsat-1 SAR images are used to monitoring of moisture acquired in May 1/1998 and May 25/1998. Radarsat-1 C band data is sensitive on moisture condition. Study area is located in Non-san site. It is made up almost agricultural area and a little of forest area. In May, Rice-planting is started in the midland of Korea. So moisture condition is undergoing many changes. Forest area need to be terrain effect removal for accurately results because it is included in layover, shadow, and so on. Results of land-cover moisture condition map are useful tool for fields of agriculture, forestry industry, and disaster.

  • PDF

Change Detection of Land-cover from Multi-temporal KOMPSAT-1 EOC Imageries

  • Ha, Sung-Ryong;Ahn, Byung-Woon;Park, Sang-Young
    • Korean Journal of Remote Sensing
    • /
    • v.18 no.1
    • /
    • pp.13-23
    • /
    • 2002
  • A radiometric correction method is developed to apply multi-temporal KOMPSAT-1 EOC satellite images for the detection of land-cover changes b\ulcorner recognizing changes in reflection pattern. Radiometric correction was carried out to eliminate the atmospheric effects that could interfere with the image properly of the satellite data acquired at different multi-times. Four invariant features of water, sand, paved road, and roofs of building are selected and a linear regression relationship among the control set images is used as a correction scheme. It is found that the utilization of panchromatic multi-temporal imagery requires the radiometric scene standardization process to correct radiometric errors that include atmospheric effects and digital image processing errors. Land-cover with specific change pattern such as paddy field is extracted by seasonal change recognition process.

Monitoring of Land-Cover Moisture Using Multi-Temporal Sar Images

  • Yoon, Bo-Yeol;Lee, Kwang-Jae;Kim, Youn-Soo;Kim, Yong-Seung
    • Korean Journal of Remote Sensing
    • /
    • v.22 no.5
    • /
    • pp.433-437
    • /
    • 2006
  • SAR image is not dependent on the weather condition and Sun's electromagnetic energy. But geometric distortions exist in almost all radar image, it need to be correction. The Radarsat-1 SAR images are used to monitoring of moisture acquired in May 1/1998 and May 25/1998. Radarsat-1 C band data is sensitive on moisture condition. Study area is located in Non-san site. It is made up almost agricultural area and a little of forest area. In May, Rice-planting is started in the midland of Korea. So moisture condition is undergoing many changes. Forest area need to be terrain effect removal for accurately results because it is included in layover, shadow, and so on. Results of land-cover moisture condition map are useful tool for fields of agriculture, forestry industry, and disaster.