• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.32-40
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• 2009

In this paper, we proposed an reconstruction algorithm of transmitted frames from displayed image on video terminal. For image quality assessment of the video streaming in the wireless network, we need information of the image that is transmitted to the end-user's device. Generally, subjective methods are widely used to evaluate the image quality by human beings because it is difficult to extract the transmitted image from the end-user's device. This paper presents an image reconstruction algerian based on the displayed image in video terminal for the extraction of the transmitted image. In the proposed method, we acquired the displayed image on video terminal using the camera. Camera-acquired images exhibit geometric and color distortions caused by characteristics of cameras and display devices. Therefore we correct the geometric distortion by exploiting the homography and color distortion by pre-computed look-up table. The experimental results show that the proposed measurement system yields promising estimation performance in terms of PSNR of $27{\sim}28dB$. We also carried out performance evaluation of the proposed method in terms of EPSNR and the quality of the estimated images by the proposed algerian was in fairly good range of MOS test scale.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.227-234
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• 2018

Recently, stitching techniques are used for obtaining wide FOV, e.g., panorama contents, from normal cameras. Despite many proposed algorithms, the no objective quality evaluation method is developed, so the comparison of algorithms are performed only in subjective way. The paper proposes a 'Delaunay-triangulation based objective assessment method' for evaluating the geometric and photometric distortions of stitched or warped images. The reference and target images are segmented by Delaunay-triangulation based on matched points between two images, the average Euclidian distance is used for geometric distortion measure, and the average or histogram of PSNR for photometric measure. We shows preliminary results with several test images and stitching methods for demonstrate the benefits and application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.211-217
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• 2006

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with urban expansion. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery. Old satellite Imagery is useful data to extract urban information. CORONA is a photo satellite reconnaissance program used from 1960 to 1972 and its imagery was declassified and has been available to the public since 1995. Since CORONA images are collected with panoramic cameras, several types of geometric distortions are involved. In this study we proposed mathematical modeling method which use modified collinearity equations. After the geometric modeling, we mosaicked images. We can successfully extract urban boundaries using GLCM method and visual interpretation in CORONA (1972) and SPOT (1995) imagery and detect urban changes in Seoul quantitatively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.260-262
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• 2003

New Image registration techniques are developed for determining geometric distortions between two images of the same scene. First, the properties of the Fourier transform of a two dimensional function under the affine transformation are given. As a result, techniques for the estimation of the coefficients of the distortion model using the spectral frequency information are developed. Image registration can be achieved by applying the fast Fourier transform (FFT) technique for cross correlation of misregistered imagery to determine spatial distances. The correlation results may be rather broad, making detection of the peak difficult, what can be suppressed by enhancing cross-correlation technique. Yield greatly improves the delectability and high precision of image misregistration.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.605-625
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• 2017

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

• Journal of Forest and Environmental Science
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• v.29 no.2
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• pp.131-137
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• 2013

This study attempts to classify forest species using hyperspectral data for supporting resources management. The primary dataset used was AISA sensor. The sensor was mounted onboard the NOMAD GAF-27 aircraft at 2,000 m altitude creating a 2 m spatial resolution on the ground. Pre-processing was carried out with CALIGEO software, which automatically corrects for both geometric and radiometric distortions of the raw image data. The radiance data set was then converted to at-sensor reflectance derived from the FODIS sensor. Spectral Angle Mapper (SAM) technique was used for image classification. The spectra libraries for tree species were established after confirming the appropriate match between field spectra and pixel spectra. Results showed that the highest spectral signature in NIR range were Kembang Semangkok (Scaphium macropodum), followed by Meranti Sarang Punai (Shorea parvifolia) and Chengal (Neobalanocarpus hemii). Meanwhile, the lowest spectral response were Kasai (Pometia pinnata), Kelat (Eugenia spp.) and Merawan (Hopea beccariana), respectively. The overall accuracy obtained was 79%. Although the accuracy of SAM techniques is below the expectation level, SAM classifier was able to classify tropical tree species. In future it is believe that the most effective way of ground data collection is to use the ground object that has the strongest response to sensor for more significant tree signatures.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.438-455
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• 2014

This study aims at providing a set of viable answers regarding the projection and cartographic scale of Daedongyeojido through a GIS-based planimetric accuracy analysis. Both global and local analyses were undertaken in the use of an analytical tool, MapAnalyst. The main results from the global analysis are threefold. First, the overall cartographic scale turned out to be between 1:158,000 and 1:162,000. Second, the rotation angles were between $2^{\circ}$ and $3^{\circ}$, and the equidistant cylindrical projection reported the smallest value. Third, in terms of position accuracy, the conformal cylindrical projection showed a best fit to the map. A local analysis was undertaken for the conformal cylindrical and equidistant azimuthal projections and its main results are threefold. First, the largest distortions in terms of the displacement vectors and distortion grid were found in the northern borderlands. Second, from the isoline maps of scales, it was acknowledged that local scales between 1:170,000 and 1:175,000 were found around the middle part of the Korean peninsula centered on Seoul. As away from the region to the north-south direction, increasingly larger scales were distributed, while the smallest ones were found in the western and eastern edges of the peninsula. Third, from the isoline maps of rotation, it was known that areas west of a northernmost city (Junggangjin) were substantially rotated to the west, while ones east of it to the east. For a more sophisticated analysis, some need to be done to have a larger set of control points, a better way of postulating the map projection, and a more advanced set of techniques for a local analysis.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.321-327
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• 2021

Wrist PA-grip view is used to diagnose triangular fibrocartilage complex (TFCC) tear because it can easily diagnose damage to the surrounding wrist ligaments. However, despite advances in radiology equipment, distortion of images due to geometric elements still has many limitations. In this paper, we propose a method that can minimize the distortions of images by analyzing the distortions occurring in the wrist PA-grip view. A source of image distance (SID) were set at 130 cm and 150 cm for comparison with 110 cm. Depending on the SID, the phantom of wrist was moved at 0, 2, 4, 6, 8, and 10 cm in the X-axis and Y-axis directions, respectively. For quantitative evaluation, the difference of distance between the radius and ulna was measured in picture archiving and communication system (PACS) system. As a qualitative evaluation, survey was conducted among 20 radiologic technologists who examined the Wrist PA-grip view. The Kruskal Wallis test was performed to compare the distortion according to the phantom movement in the X-axis and Y-axis directions based on the SID, and the Tukey test was performed as a post-test. In the quantitative evaluation results, the measured values obtained in the X-axis was not significantly different in all groups (p>0.05). The measured values obtained in the Y-axis was significantly different in the most groups (p<0.05). Therefore, to reduce distortion while maintaining image quality, we recommend what examine the SID at 150 cm than 110 cm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2663-2678
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• 2012

Due to sharp depth transition, big holes may be found in the novel view that is synthesized by depth-image-based rendering (DIBR). A hole-filling method based on disparity map is proposed. One important aspect of the method is that the disparity map of destination image is used for hole-filling, instead of the depth image of reference image. Firstly, the big hole detection based on disparity map is conducted, and the start point and the end point of the hole are recorded. Then foreground pixels and background pixels are distinguished for hole-dilating according to disparity map, so that areas with matching errors can be determined and eliminated. In addition, parallaxes of pixels in the area with holes and matching errors are changed to new values. Finally, holes are filled with background pixels from reference image according to these new parallaxes. Experimental results show that the quality of the new view after hole-filling is quite well; and geometric distortions are avoided in destination image, in contrast to the virtual view generated by depth-smoothing methods and image inpainting methods. Moreover, this method is easy for hardware implementation.