• 제목/요약/키워드: cover image

검색결과 711건 처리시간 0.04초

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

  • Munkbaatar, Doyoddorj;Park, Young-Ho;Rhee, Kyung-Hyune
    • 한국멀티미디어학회논문지
    • /
    • 제15권7호
    • /
    • pp.891-902
    • /
    • 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.

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

  • 조형갑;김동욱;신정일
    • 대한공간정보학회지
    • /
    • 제22권3호
    • /
    • pp.155-160
    • /
    • 2014
  • 본 논문에서는 각기 다른 3가지 해상도로 촬영된 항공 초분광영상을 이용하여 건물, 도로, 산림 등 8가지 분류군에 대해 토지피복분류를 실시하고 정확도를 비교하는 연구를 수행하였다. 연구는 24밴드(0.5m 공간해상도), 48밴드(1.0m 공간해상도), 96밴드(1.5m 공간해상도)로 각각 1000m, 2000m, 3000m고도에서 촬영된 초분광영상을 이용하여 8가지 클래스에 대해 토지피복분류를 수행하였다. 그 결과 2000m고도에서 촬영된 48밴드 초분광영상을 이용하여 분류한 영상이 가장 높은 분류정확도를 보였고, 24밴드, 96밴드 순으로 분류정확도가 높게 나타났다. 초분광영상 활용에 있어서 1m 공간해상도에 48개밴드를 사용하여 토지피복분류를 수행함에 있어 적합함을 확인하였고 항공 초분광영상을 활용한 주제도 제작과 관련하여 정확도와 실용성 면에서 공간정보 품질이 개선될 것으로 기대한다.

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)
    • /
    • 제15권3호
    • /
    • pp.1051-1077
    • /
    • 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.

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

  • 전성우;김귀곤;박종화;이동근
    • 한국환경복원기술학회지
    • /
    • 제2권1호
    • /
    • pp.29-37
    • /
    • 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.

  • PDF

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

  • 이현직;유지호;유영걸
    • 한국측량학회:학술대회논문집
    • /
    • 한국측량학회 2010년 춘계학술발표회 논문집
    • /
    • pp.277-280
    • /
    • 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.

  • PDF

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

  • 강주형;김민성;김성진;곽수영
    • 전기전자학회논문지
    • /
    • 제27권4호
    • /
    • pp.456-463
    • /
    • 2023
  • 본 논문에서는 사용자의 개입없이 고해상도 위성 영상을 활용하여 정밀한 토지피복분류를 위해 U-Net 네트워크 모델에 SPADE 구조를 결합한 SSResUNet 모델을 제안한다. 제안하는 네트워크는 위성 영상의 공간적 특성을 보존하여 복잡도가 높은 환경에서도 강인한 분류모델이라는 장점이 있다. 다목적실용위성 3A 영상을 통해 학습한 결과 기존 U-Net, U-Net++ 대비 뛰어난 결과를 보였으며 평균 IoU 76.10, Dice 86.22의 성능을 도출하였다.

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

  • 조홍제;김광섭;이충희
    • 한국수자원학회논문집
    • /
    • 제34권6호
    • /
    • pp.735-743
    • /
    • 2001
  • CN법은 토지이용변화로 인한 수문학적 영향을 판단하는 경우, 그 적용성이 매우 우수한 것으로 알려져 있다. 본 연구에서는 토지이용의 공간적분포를 분석하기 위해 Landsat 다중분광영상을 이용하였다. 분석된 영상자료로부터 산지지역을 식생밀도에 따라 재분류하고, 식생밀도가 유출에 미치는 영향을 분석하기 위해 CN법을 이용하였다. 토양도의 종류(정밀토양도, 개략토양도)에 따라 분석한 결과, CN은 식생밀도에 따라서는 변화가 미미한 반면 토양 도의 종류에 따라서는 매우 큰 차이를 보였다. 실측강우·유출자료와 비교해본 결과 CN추정에 있어 정밀토양도를 사용하는 것이 향상된 결과를 보였다.

  • PDF

Linear Spectral Mixture Analysis of Landsat Imagery for Wetland land-Cover Classification in Paldang Reservoir and Vicinity

  • Kim, Sang-Wook;Park, Chong-Hwa
    • 대한원격탐사학회지
    • /
    • 제20권3호
    • /
    • pp.197-205
    • /
    • 2004
  • Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.