• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.51-76
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• 2009

In this paper, a new hybrid opto-digital multiple information hiding and real-time extracting system was suggested and implemented using a volume holographic optical correlator. The multiple information hiding system in which the multiple information can be hided in an arbitrary cover image was digitally implemented by using the combination of pseudo random sequence and Hadamard matrix. In addition, a real-time optical extraction system in which the hided multiple information in a cover image can be extracted in real-time was implemented by using a volume holographic optical correlator. In the VanderLugt-type holographic optical correlator used in this experiment, the multiful matched spatial filters corresponding each of the hided informations were recorded in a photorefractive crystal by using the moving window-based angular multiplexing scheme.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.1-10
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• 2014

In this paper, we propose a new view synthesis technique for coding of multi-view color and depth data in arbitrary camera arrangements. We treat each camera position as a 3-D point in world coordinates and build clusters of those vertices. Color and depth data within a cluster are gathered into one camera position using a hierarchical representation based on the concept of layered depth image (LDI). Since one camera can cover only a limited viewing range, we set multiple reference cameras so that multiple LDIs are generated to cover the whole viewing range. Therefore, we can enhance the visual quality of the reconstructed views from multiple LDIs comparing with that from a single LDI. From experimental results, the proposed scheme shows better coding performance under arbitrary camera configurations in terms of PSNR and subjective visual quality.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.733-741
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• 2012

The successful launch of Arirang satellites allow the acquisition of high resolution satellite imagery of Korean territory and enables the transition from the conventional cultivation area survey method to new image based methods adopted in advanced nations. In this study, we suggested reasonable sizes of the primary sampling unit and the secondary sampling unit for the satellite imagery based sampling design in 8 provinces preselected for this research. The PSU size was determined mainly in consideration of intracorrelation that shows the degree of homogeneity within each cluster and the efficiency of the image process. For the SSU size, we considered the relative standard error and the differences between the land cover maps produced by the Ministry of Environment and the satellite imagery processed by the National Statistical Office.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.355-363
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• 2007

The 3D DWT(The Three Dimensional Discrete Wavelet Transform) scheme is potentially regarded as useful one on analyzing both spatial and spectral information. Nevertheless, few researchers have attempted to process or classified remotely sensed images using the 3D DWT. This study aims to apply the 3D DWT to the land cover classification of optical and SAR(Synthetic Aperture Radar) images. Then, their results are evaluated quantitatively and compared with the results of traditional classification technique. As the experimental results, the 3D DWT shows superior classification results to conventional techniques, especially dealing with the high-resolution imagery and SAR imagery. It is thought that the 3D DWT scheme can be extended to multi-temporal or multi-sensor image classification.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.83-89
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• 2005

This study utilized a spatial region growing segmentation and a classification using fuzzy membership vectors to detect the changes in the images observed at different dates. Consider two co-registered images of the same scene, and one image is supposed to have the class map of the scene at the observation time. The method performs the unsupervised segmentation and the fuzzy classification for the other image, and then detects the changes in the scene by examining the changes in the fuzzy membership vectors of the segmented regions in the classification procedure. The algorithm was evaluated with simulated images and then applied to a real scene of the Korean Peninsula using the KOMPSAT-l EOC images. In the expertments, the proposed method showed a great performance for detecting changes in land-cover.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.580-583
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• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ 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. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.189-197
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• 2001

Generally, remote sensing is useful to obtain the quantitative and qualitative information of a wide area. For monitoring earth resources and environment, land cover classification of remotely sensed data are needed over increasingly larger area. The objective this study is to propose the process for land cover classification method over a wide area using multi-scene satellite data. Land cover of Korean peninsula was extracted from a Landsat TM and ETM+ mosaic created from 23 scenes at 100-meter resolution. Well-known techniques that used to general image processing and classification are applied to this wide area classification. It is expected that these process is very useful to promptly and efficiently grasp of small scale spatial information such as national territorial information.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.181-183
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• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.168-173
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• 2011

In this paper, an optical image hiding technique using real-valued decoding key is proposed. In the embedding process, a each zero-padded original image placed in a quadrants on an input plane is multiplied by a statistically independent random phase pattern and is Fourier transformed. An encoded image is obtained by taking the real-valued data from the Fourier transformed image. And then a phase-encoded pattern, used as a hidden image and a decoding key, is generated by the use of multiple phase wrapping from the encoded images. A transmitted image is made from the linear superposition of the weighted hidden images and a cover image. In reconstruction process, the mirror reconstructed images can be obtained at two quadrants by the inverse-Fourier transform of the product of the transmitted image and the decoding key. Computer simulation and optical experiment are demonstrated in order to confirm the proposed technique.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.