• Title/Summary/Keyword: Cover-image

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The Comparison of Water Quality of Daecheong-Dam basin According to the Data Sources of Land Cover Map (토지피복도 자료원에 따른 대청댐유역 수질특성 비교)

  • Lee, Geun Sang;Park, Jin Hyeog;Choi, Yun Woong
    • Spatial Information Research
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    • v.20 no.5
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    • pp.25-35
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    • 2012
  • This study compared the influence of water quality according to the data sources of spatial information. Firstly, land cover map was constructed through image classification of Daecheong-dam basin and the accuracy of image classification from satellite image showed high as 88.76% in comparison with the large-scaled land cover map in Ministry of Environment, to calculate Event Mean Concentration (EMC) by land cover that impact on the evaluation of nonpoint source pollutant loads. Also curve number and direct runoff were calculated by spatial overlay with soil map and land cover map from image classification. And Seokcheon and Daecheong-Dam basin showed high in the analysis of curve number and direct runoff. Samgacheon-Joint and Sokcheon-Downstream basin showed high in the nonpoint source pollutant loads of BOD from direct runoff and EMC. And Samgacheon-Joint and Bonghwangcheon- Downstream basin showed high in the nonpoint source pollutant loads of TN and TP. Nonpoint source pollutant loads from image classification were compared with those by the land cover map from Ministry of Environment to present the effectivity of nonpoint source pollutant loads from satellite image. And Daecheong-Dam Upstream basin showed high as 10.64%, 11.70% and 20.00% respectively in the errors of nonpoint source pollutant loads of BOD, TN, and TP. Therefore, it is desirable that spatial information including with paddy and dry field is applied to the evaluation of nonpoint source pollutant loads in order to simulate water quality of basin effectively.

Review of Land Cover Classification Potential in River Spaces Using Satellite Imagery and Deep Learning-Based Image Training Method (딥 러닝 기반 이미지 트레이닝을 활용한 하천 공간 내 피복 분류 가능성 검토)

  • Woochul, Kang;Eun-kyung, Jang
    • Ecology and Resilient Infrastructure
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    • v.9 no.4
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    • pp.218-227
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    • 2022
  • This study attempted classification through deep learning-based image training for land cover classification in river spaces which is one of the important data for efficient river management. For this purpose, land cover classification analysis with the RGB image of the target section based on the category classification index of major land cover map was conducted by using the learning outcomes from the result of labeling. In addition, land cover classification of the river spaces was performed by unsupervised and supervised classification from Sentinel-2 satellite images provided in an open format, and this was compared with the results of deep learning-based image classification. As a result of the analysis, it showed more accurate prediction results compared to unsupervised classification results, and it presented significantly improved classification results in the case of high-resolution images. The result of this study showed the possibility of classifying water areas and wetlands in the river spaces, and if additional research is performed in the future, the deep learning based image train method for the land cover classification could be used for river management.

Evidential Fusion of Multsensor Multichannel Imagery

  • Lee Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.22 no.1
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    • pp.75-85
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    • 2006
  • This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

Reversible data hiding algorithm using spatial locality and the surface characteristics of image

  • Jung, Soo-Mok;On, Byung-Won
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.8
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    • pp.1-12
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    • 2016
  • In this paper, we propose a very efficient reversible data hiding algorithm using spatial locality and the surface characteristics of image. Spacial locality and a variety of surface characteristics are present in natural images. So, it is possible to precisely predict the pixel value using the locality and surface characteristics of image. Therefore, the frequency is increased significantly at the peak point of the difference histogram using the precisely predicted pixel values. Thus, it is possible to increase the amount of data to be embedded in image using the spatial locality and surface characteristics of image. By using the proposed reversible data hiding algorithm, visually high quality stego-image can be generated, the embedded data and the original cover image can be extracted without distortion from the stego-image, and the embedding data are much greater than that of the previous algorithm. The experimental results show the superiority of the proposed algorithm.

A Study on Confidential Data Hiding Technique with Spatial Encryption for Color Image

  • Jung, Soo-Mok
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.1
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    • pp.85-88
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    • 2019
  • In this paper, we propose a technique for spatially encrypting confidential data into R, G, B planes of color image and extracting spatially encrypted confidential data. The effectiveness of the proposed technique is verified by mathematically analyzing the quality of the stego-image generated using the proposed technique. The proposed technique can hide confidential data securely into cover image by spatially encrypting the confidential data, and can extract confidential data from the stego-image. The quality of the stego-image created by applying the proposed technique is very good. The average value of the quality of the stego-image is 51.14 dB. Therefore, it is not visually recognizable whether the confidential data is hidden in the stego-image. The proposed technique can be widely used for military and intellectual property protection.

An Improved Reversible Data Hiding Technique using Histogram Characteristics and Double Encryption Technique

  • Soo-Mok Jung
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.132-139
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    • 2024
  • In this paper, we proposed an effective technique that uses location-based encryption technique and spatial encryption technique to improve security vulnerabilities in previous reversible data hiding technique that can hide twice as much confidential data as the NSAS technique. If the proposed technique is applied to hide confidential data in an image, the same amount of confidential data can be hidden compared to the previous technique, but the security of confidential data is greatly enhanced. By hiding confidential data in an image using the proposed technique, high-quality stego-image can be generated, making it impossible to visually distinguish whether confidential data is hidden in the image. Additionally, confidential data can be restored from stego-image without loss, and the original cover image can also be restored without loss. Through experiments, it was confirmed that when confidential data is hidden by applying the proposed technique, the quality of the stego-image is maintained up to 39.73dB, and the security of the stego-image is greatly strengthened.

A Fundamental Study on the Influence of Fresh Concrete Quality Properties due to the Cover of Concrete Mixer Truck (콘크리트 믹서 트럭 덮개의 유무가 콘크리트 품질 특성에 미치는 영향에 관한 기초연구)

  • Chae, Young-Suk;Lim, Byung-Hoon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.14 no.6
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    • pp.198-204
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    • 2010
  • The cover of truck agitator give in a part to prevent the lower flowing of fresh concrete when the concrete are transported from the ready mixed concrete plant to the construction field. As a result of the question data, it show up a dirty image to the general civil society. Due to the above image, it is predicted to affect the image of the construction company, so we did the site experiment of the flowing, the amounts of air, the temperature change of concrete with the concrete left in the site, to find out the usefulness. Also, for the comparing with this, we got the result by doing the inner experiment with the same condition. As the result of the experiment, the cover of truck agitator affect little to the reduction of slump. The change of the air amount, regardless of the existence of cover, was not effected much in proper level until 60minutes. In addition, The compression strength was proper to the goal design strength until 90minutes regardless of the cover of truck agitator exist or not exist.

Water Column Correction of Airborne Hyperspectral Image for Benthic Cover Type Classification of Coastal Area (연안 해저 피복 분류를 위한 항공 초분광영상의 수심보정)

  • Shin, Jung Il;Cho, Hyung Gab;Kim, Sung Hak;Choi, Im Ho;Jung, Kyu Kui
    • Spatial Information Research
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    • v.23 no.2
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    • pp.31-38
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    • 2015
  • Remote sensing data is used to increasing efficiency on benthic cover type survey. Satellite and aerial imagery has variance of reflectance by water column effect even if bottom is consisted with same cover type and condition. This study tried to analyze advances of surveying extent and accuracy through water column correction of CASI-1500 hyperspectral image. Study area is coast of Gangneung city, South Korea where benthic environment is rapidly changing with bleaching of coral reef. Water column correction coefficient was estimated using regression models between water reflectance ($R_W$) and depth for sand bottom then the coefficients were applied to whole image. The results shows that expanded interpretable depth from 6-7m to 15m and decreased variation of reflectance by depth. Additionally, water column corrected reflectance image shows 13%p increased accuracy on benthic cover type classification.

Matching Techniques with Land Cover Image for Improving Accuracy of DEM Generation from IKONOS Imagery (IKONOS 영상을 이용한 DEM 추출의 정확도 향상을 위한 토지피복도 활용 정합기법)

  • Lee, Hyo Seong;Park, Byung Uk;Han, Dong Yeob;Ahn, Ki Weon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1D
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    • pp.153-160
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    • 2009
  • In relation to digital elevation model(DEM) production using high resolution satellite imagery, existing studies present that DEM accuracy differently show according to land cover property. This study therefore proposes auto-selection method of window size for correlation matching according to land cover property of IKONOS Geo-level stereo image. For this, land cover classified image is obtained by IKONOS color image with four bands. In addition, correlation-coefficients are computed at regular intervals in pixels of the window-search area to shorten of matching time. As the results, DEM by the proposed method showed more accurate than DEM using the fixed window-size matching. We estimate that accuracy of the proposed DEM improved more than DEM by digital map and ERDAS in agricultural land.

An Improved Reversible Data Hiding Technique using Histogram Characteristics of Image

  • Soo-Mok, Jung
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.63-69
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    • 2023
  • In this paper, we propose an effective reversible data hiding technique that increases the confidential data hiding amount of the NSAS technique itself by utilizing the characteristics of image. The proposed technique shifts the histogram using multiple zeros of the histogram and hides 2 bits of confidential data at each peak point. Using the proposed technique, the amount of confidential data that can be hidden is doubled compared to the existing technique, and high-quality stego-image can be created. Confidential data can be restored without loss from the stego- image, and the original cover image can be restored without loss. Through experiments, it was confirmed that the proposed technique can hide twice as much confidential data than the existing technique, and the image quality of the stego-image is very good with a maximum of 39.75dB.