• Title/Summary/Keyword: Cover image

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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
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    • v.22 no.5
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    • pp.433-437
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    • 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.

A Robust Reversible Data Hiding Scheme with Large Embedding Capacity and High Visual Quality

  • Munkbaatar, Doyoddorj;Park, Young-Ho;Rhee, Kyung-Hyune
    • Journal of Korea Multimedia Society
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    • v.15 no.7
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    • pp.891-902
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    • 2012
  • Reversible data hiding scheme is a form of steganography in which the secret embedding data can be retrieved from a stego image for the purpose of identification, copyright protection and making a covert channel. The reversible data hiding should satisfy that not only are the distortions due to artifacts against the cover image invisible but also it has large embedding capacity as far as possible. In this paper, we propose a robust reversible data hiding scheme by exploiting the differences between a center pixel and its neighboring pixels in each sub-block of the image to embed secret data into extra space. Moreover, our scheme enhances the embedding capacity and can recover the embedded data from the stego image without causing any perceptible distortions to the cover image. Simulation results show that our proposed scheme has lower visible distortions in the stego image and provides robustness to geometrical image manipulations, such as rotation and cropping operations.

Study of Comparison of Classification Accuracy of Airborne Hyperspectral Image Land Cover Classification though Resolution Change (해상도변화에 따른 항공초분광영상 토지피복분류의 분류정확도 비교 연구)

  • Cho, Hyung Gab;Kim, Dong Wook;Shin, Jung Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.3
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    • pp.155-160
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    • 2014
  • This paper deals with comparison of classification accuracy between three land cover classification results having difference in resolution and they were classified with eight classes including building, road, forest, etc. Airborne hyperspectral image used in this study was acquired at 1000m, 2000m, 3000m elevation and had 24 bands(0.5m spatial resolution), 48 bands(1.0m), 96 bands(1.5m). Assessment of classification accuracy showed that the classification using 48 bands hyperspectral image had outstanding result as compared with other images. For using hyperspectral image, it was verified that 1m spatial resolution image having 48 bands was appropriate to classify land cover and qualitative improvement is expected in thematic map creation using airborne hyperspectral image.

Novel Secure Hybrid Image Steganography Technique Based on Pattern Matching

  • Hamza, Ali;Shehzad, Danish;Sarfraz, Muhammad Shahzad;Habib, Usman;Shafi, Numan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.1051-1077
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    • 2021
  • The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

A Theoretical Study on Land Cover Classification - Focused on Natural Environment Management - (토지피복분류에 관한 이론적 연구 - 자연환경관리를 중심으로 -)

  • Jeon, Seong-Woo;Kim, Kwi-Gon;Park, Chong-Hwa;Lee, Dong-Kun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.2 no.1
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    • pp.29-37
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    • 1999
  • Land cover classification is an essential basic information in natural environment management; however, land cover classification studies in Korea have not yet been proceeded to a sufficient level. At the present, only a limited number of the precedent studies that only cover definite city area has been conducted. Furthermore, there is almost no research conducted on the land cover classification schemes that could accurately classify the Korea's land cover conditions. This study primarily focuses on the land cover classification scheme which carries the most urgent priority in order to classify and to map out the Korean land cover conditions. In order to develop the most suitable land cover classification scheme, many foreign land cover classification cases and projects that are being carried out were reviewed in depth. The land cover classification scheme this study proposes comprises 3 levels : The first level consists of 7 different classes; the second level consists of 22 different classes; and the third level is made up of 50 classes. The land cover classification map will serve many important roles in natural environment management, such as the conjecture of natural habitats and estimation of oxygen production or carbon dioxide absorption capability of a forest. In water pollution modelling, the land cover classification data can be used to estimate and locate non-point sources of water pollution. If applied to a watershed, modelling it will allow to estimate the total amount of pollution from non-point sources of pollution in the water shed. The land cover classification data will also be good as a barometer data that determines defusion of air pollutants in air pollution modelling.

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Automatic Extraction of Land Cover information By Using KOMPSAT-2 Imagery (KOMPSAT-2 영상을 이용한 토지피복정보 자동 추출)

  • Lee, Hyun-Jik;Ru, Ji-Ho;Yu, Young-Geol
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.277-280
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    • 2010
  • There is a need to convert the old low- or medium-resolution satellite image-based thematic mapping to the high-resolution satellite image-based mapping of GSD 1m grade or lower. There is also a need to generate middle- or large-scale thematic maps of 1:5,000 or lower. In this study, the DEM and orthoimage is generated with the KOMPSAT-2 stereo image of Yuseong-gu, Daejeon Metropolitan City. By utilizing the orthoimage, automatic extraction experiments of land cover information are generated for buildings, roads and urban areas, raw land(agricultural land), mountains and forests, hydrosphere, grassland, and shadow. The experiment results show that it is possible to classify, in detail, for natural features such as the hydrosphere, mountains and forests, grassland, shadow, and raw land. While artificial features such as roads, buildings, and urban areas can be easily classified with automatic extraction, there are difficulties on detailed classifications along the boundaries. Further research should be performed on the automation methods using the conventional thematic maps and all sorts of geo-spatial information and mapping techniques in order to classify thematic information in detail.

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Land Cover Classification of Satellite Image using SSResUnet Model (SSResUnet 모델을 이용한 위성 영상 토지피복분류)

  • Joohyung Kang;Minsung Kim;Seongjin Kim;Sooyeong Kwak
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.456-463
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    • 2023
  • In this paper, we introduce the SSResUNet network model, which integrates the SPADE structure with the U-Net network model for accurate land cover classification using high-resolution satellite imagery without requiring user intervention. The proposed network possesses the advantage of preserving the spatial characteristics inherent in satellite imagery, rendering it a robust classification model even in intricate environments. Experimental results, obtained through training on KOMPSAT-3A satellite images, exhibit superior performance compared to conventional U-Net and U-Net++ models, showcasing an average Intersection over Union (IoU) of 76.10 and a Dice coefficient of 86.22.

A Study of Runoff Curve Number Estimation Using Landsat Image (LANDSAT 영상을 이용한 CN값 산정에 관한 연구)

  • Jo, Hong-Je;Kim, Gwang-Seop;Lee, Chung-Hui
    • Journal of Korea Water Resources Association
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    • v.34 no.6
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    • pp.735-743
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    • 2001
  • CN procedure has been proven to be useful method for evaluating the effects of changes in land-use and treatment on hydrology. In this study, the use of Landsat multi-spectral image was investigated for analyzing the land-use distribution. From the Landsat data, forest areas were classified according to the density of trees. Watershed CN's were calculated to analyze the effects of the density of trees and soil cover types on direct runoff. According to the results, the density of trees had a little effect while soil cover types had a large effect on CN, From the comparison of estimated runoffs from CN method with observed runoffs, detailed soil cover map provides improved results.

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