• Title/Summary/Keyword: Cover image

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Steganalysis Using Joint Moment of Wavelet Subbands (웨이블렛 부밴드의 조인트 모멘트를 이용한 스테그분석)

  • Park, Tae-Hee;Hyun, Seung-Hwa;Kim, Jae-Ho;Eom, Il-Kyu
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.3
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    • pp.71-78
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    • 2011
  • This paper propose image steganalysis scheme based on independence between parent and child subband on the multi-layer wavelet domain. The proposed method decompose cover and stego images into 12 subbands by applying 3-level Haar UWT(Undecimated Wavelet Transform), analyze statistical independency between parent and child subband. Because this independency is appeared more difference in stego image than in cover image, we can use it as feature to differenciate between cover and stego image. Therefore we extract 72D features by calculation first 3 order statistical moments from joint characteristic function between parent and child subband. Multi-layer perceptron(MLP) is applied as classifier to discriminate between cover and stego image. We test the performance of proposed scheme over various embedding rates by the LSB, SS, BSS embedding method. The proposed scheme outperforms the previous schemes in detection rate to existence of hidden message as well as exactness of discrimination.

Analysis of Land-cover Types Using Multistage Hierarchical flustering Image Classification (다단계 계층군집 영상분류법을 이용한 토지 피복 분석)

  • 이상훈
    • Korean Journal of Remote Sensing
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    • v.19 no.2
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    • pp.135-147
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    • 2003
  • This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.

FPGA Implementation of LSB-Based Steganography

  • Vinh, Quang Do;Koo, Insoo
    • Journal of information and communication convergence engineering
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    • v.15 no.3
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    • pp.151-159
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    • 2017
  • Steganography, which is popular as an image processing technology, is the art of using digital images to hide a secret message in such a way that its existence can only be discovered by the sender and the intended receiver. This technique has the advantage of concealing secret information in a cover medium without drawing attention to it, unlike cryptography, which tries to convert data into something messy or meaningless. In this paper, we propose two efficient least significant bit (LSB)-based steganography techniques for designing an image-based steganography system on chip using hardware description language (HDL). The proposed techniques manipulate the LSB plane of the cover image to embed text inside it. The output of these algorithms is a stego-image which has the same quality as that of the original image. We also implement the proposed techniques using the Altera field programmable gate array (FPGA) and Quartus II design software.

Application and Development of Integration Technique to Generate Land-cover and Soil Moisture Map Using High Resolution Optical and SAR images

  • Kim Ji-Eun;Park Sang-Eun;Kim Duk-jin;Kim Jun-su;Moon Wooil M.
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.497-500
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    • 2005
  • Research and development of remote sensing technique is necessary so that more accurate and extensive information may be obtained. To achieve this goal, the synthesized technique which integrates the high resolution optic and SAR image, and topographical information was examined to investigate the quantitative/qualitative characteristics of the Earth's surface environment. For this purpose, high-precision DEMs of Jeju-Island was generated and data fusion algorithm was developed in order to integrate the multi-spectral optic and polarimetric SAR image. Three dimensional land-cover and two dimensional soil moisture maps were generated conclusively so as to investigate the Earth's surface environments and extract the geophysical parameters.

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Increasing Spatial Resolution of Remotely Sensed Image using HNN Super-resolution Mapping Combined with a Forward Model

  • Minh, Nguyen Quang;Huong, Nguyen Thi Thu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.6_2
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    • pp.559-565
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    • 2013
  • Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

Analysis of Land Cover Change in the Waterfront Area of Taehwa River using Hyperspectral Image Information (초분광 영상정보를 이용한 태화강 수계지역의 토지피복 변화분석)

  • KIM, Yong-Suk
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.1
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    • pp.12-25
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    • 2021
  • Land cover maps are used in various fields in urban expansion and development. This study analyzed the amount of land cover change over time using multi-sensor information, focusing on the waterfront area of the Taehwa River. In order to apply high-accuracy aerial hyperspectral images, patterns with Field-spectral were reviewed and compared with time series Digital map. The hyperspectral image was set as 13 land cover grades, and the time series digital map was classified into 7 and the waterfront area was classified into 5-6 grades and analyzed. As a result of analysis of the change in land cover of the digital map from the 1990s to 2010, it was found that forest areas were rapidly decreasing and Farmland and grassland were becoming urban. As for the land cover change(2010~2019) in the waterfront area(set 500m) analyzed through hyperspectral images, it was found that Farmland(1.4㎢), Forest(1.0㎢), and grassland (0.8㎢) were converted into urbanized and dried areas, and urbanization was accelerating around the Taehwa River waterfront. Recently, a lot of research has been conducted on the production of land cover maps using high-precision satellite images and aerial hyperspectral images, so it is expected that more detailed and precise land cover maps can be produced and utilized.

A Comparative Study on Suitable SVM Kernel Function of Land Cover Classification Using KOMPSAT-2 Imagery (KOMPSAT-2 영상의 토지피복분류에 적합한 SVM 커널 함수 비교 연구)

  • Kang, Nam Yi;Go, Sin Young;Cho, Gi Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.2
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    • pp.19-25
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    • 2013
  • Recently, the high-resolution satellite images is used the land cover and status data for the natural resources or environment management very helpful. The SVM algorithm of image processing has been used in various field. However, classification accuracy by SVM algorithm can be changed by various kernel functions and parameters. In this paper, the typical kernel function of the SVM algorithm was applied to the KOMPSAT-2 image and than the result of land cover performed the accuracy analysis using the checkpoint. Also, we carried out the analysis for selected the SVM kernel function from the land cover of the target region. As a result, the polynomial kernel function is demonstrated about the highest overall accuracy of classification. And that we know that the polynomial kernel and RBF kernel function is the best kernel function about each classification category accuracy.

Method Development of Land Cover Change Detection by Typhoon RUSA (태풍 RUSA 전.후의 토지피복변화 분석기법 연구)

  • Lee, Mi-Seon;Park, Geun-Ae;Jung, In-Kyun;Kim, Seong-Joon
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2003.10a
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    • pp.75-78
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    • 2003
  • This study is to present a method of land cover change detection by the typhoon RUSA (August 1 - September 4, 2002) using Landsat 7 ETM+ images. For the Namdae-cheon watershed in Gangreung, two images of Sept. 29, 2000 and Nov. 22, 2002 were prepared. To identify the damaged areas, firstly, the NDVI (Normalized Difference Vegetation Index) of each image was computed, secondly, the NDVI values were reclassified as two categories that the negative index values including zero are the one and the positive index values are the other, thirdly the reclassified image before typhoon is subtracted from the reclassified image after typhoon to get DNDVI (Differential NDVI). From the DNDVI image, the flooded and damaged areas could be extracted.

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Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

  • Kasana, Geeta;Singh, Kulbir;Bhatia, Satvinder Singh
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1331-1344
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    • 2017
  • In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.

High Capacity Information Hiding Method Based on Pixel-value Adjustment with Modulus Operation

  • Li, Teng;Zhang, Yu;Wang, Sha;Sun, Jun-jie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1521-1537
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    • 2021
  • Through information hiding technique, secret message can be hidden in pictures. Stego-image quality and hiding capacity are two important metrics for information hiding. To enhance these metrics, many schemes were proposed by scholars in recent years. Some of them are effective and successful, but there is still a room for further improvement. A high capacity information hiding scheme (PAMO, Pixel-value Adjustment with Modulus Operation Algorithm) is introduced in this paper. PAMO scheme uses pixel value adjustment with modulus operation to hide confidential data in cover-image. PAMO scheme and some referenced schemes are implemented in Python and experiments are carried out to evaluate their performance. In the experiments, PAMO scheme shows better performance than other methods do. When secret message length is less than 72000 bits, the highest hiding capacity of PAMO can reach 7 bits per pixel, at the same time the PSNR of stego-images is greater than 30 dB.