• Applied Microscopy
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• v.50
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• pp.23.1-23.9
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• 2020

We propose an effective deep learning model to denoise scanning transmission electron microscopy (STEM) image series, named Noise2Atom, to map images from a source domain 𝓢 to a target domain 𝓒, where 𝓢 is for our noisy experimental dataset, and 𝓒 is for the desired clear atomic images. Noise2Atom uses two external networks to apply additional constraints from the domain knowledge. This model requires no signal prior, no noise model estimation, and no paired training images. The only assumption is that the inputs are acquired with identical experimental configurations. To evaluate the restoration performance of our model, as it is impossible to obtain ground truth for our experimental dataset, we propose consecutive structural similarity (CSS) for image quality assessment, based on the fact that the structures remain much the same as the previous frame(s) within small scan intervals. We demonstrate the superiority of our model by providing evaluation in terms of CSS and visual quality on different experimental datasets.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.114-123
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• 2014

Vehicle Black Box (Event Data Recorder EDR) only recognizes the general surrounding environments of load. In addition, general EDR is difficult to recognize the images of a sudden illumination change. It appears that the lens is being a severe distortion. Therefore, general EDR does not provide the clues of the circumstances of the accident. To solve this problem, we estimate the value of Normalized Luminance Descriptor(NLD) and Normalized Contrast Descriptor(NCD). Illumination change is corrected using Normalized Image Quality(NIQ). Second, we are corrected lens distortion using model of Field Of View(FOV) based on designed method of fisheye lens. As a result, we propose integration algorithm of two methods that correct distortions of images using each Gamma Correction and Lens Correction in parallel.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.4
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• pp.29-42
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• 2017

As the "Guidelines for GHG Environmental Assessment" was revised, it pointed out that the developers should evaluate GHG sequestration and storage of the developing site. However, the current guidelines only taking into account the quantitative reduction lost within the development site, and did not consider the qualitative decrease in the carbon sequestration capacity of forest edge produced by developments. In order to assess the quantitative and qualitative effects of vegetation carbon uptake, the CASA-NPP model and satellite image spatial-temporal fusion were used to estimate the annual net primary production in 2005 and 2015. The development projects between 2006 and 2014 were examined for evaluate quantitative changes in development site and qualitative changes in surroundings by development types. The RMSE value of the satellite image fusion results is less than 0.1 and approaches 0, and the correlation coefficient is more than 0.6, which shows relatively high prediction accuracy. The NPP estimation results range from 0 to $1335.53g\;C/m^2$ year before development and from 0 to $1333.77g\;C/m^2$ year after development. As a result of analyzing NPP reduction amount within the development area by type of forest development, the difference is not significant by type of development but it shows the lowest change in the sports facilities development. It was also found that the vegetation was most affected by the edge vegetation of industrial development. This suggests that the industrial development causes additional development in the surrounding area and indirectly influences the carbon sequestration function of edge vegetaion due to the increase of the edge and influx of disturbed species. The NPP calculation method and results presented in this study can be applied to quantitative and qualitative impact assessment of before and after development, and it can be applied to policies related to greenhouse gas in environmental impact assessment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2547-2567
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• 2021

It has been widely acknowledged that occlusion impairments adversely distress many face recognition algorithms' performance. Therefore, it is crucial to solving the problem of face image occlusion in face recognition. To solve the image occlusion problem in face recognition, this paper aims to automatically de-occlude the human face majority or discriminative regions to improve face recognition performance. To achieve this, we decompose the generative process into two key stages and employ a separate generative adversarial network (GAN)-based network in both stages. The first stage generates an initial coarse face image without an occlusion mask. The second stage refines the result from the first stage by forcing it closer to real face images or ground truth. To increase the performance and minimize the artifacts in the generated result, a new refine loss (e.g., reconstruction loss, perceptual loss, and adversarial loss) is used to determine all differences between the generated de-occluded face image and ground truth. Furthermore, we build occluded face images and corresponding occlusion-free face images dataset. We trained our model on this new dataset and later tested it on real-world face images. The experiment results (qualitative and quantitative) and the comparative study confirm the robustness and effectiveness of the proposed work in removing challenging occlusion masks with various structures, sizes, shapes, types, and positions.

• Journal of Dental Rehabilitation and Applied Science
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• v.34 no.3
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• pp.208-217
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• 2018

The maxillary anterior teeth play an important role in esthetics. The esthetic of maxillary anterior teeth is closely related to tooth morphology and also harmony with gingiva. Precise diagnosis and treatment plan are essential to satisfy patient's demand, and sometimes surrounding soft tissue management is involved to achieve the goal. Gingivectomy can be considered as one method to make esthetic restoration possible. As well as esthetics, function has to be considered in maxillary anterior teeth restoration. Definitive cast of abutment and diagnostic cast waxed up labially were superimposed with model scanner, so can provide former comfortable occlusion. This case report demonstrates functional and esthetic improvements of two patients through gingivectomy and the data of superimposed image of casts.

• Journal of Ecology and Environment
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• v.41 no.4
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• Journal of Internet of Things and Convergence
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• v.4 no.2
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• pp.1-6
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• 2018

Techniques for generating new sample data from higher dimensional data such as images have been utilized variously for speech synthesis, image conversion and image restoration. This paper adopts Progressive Growing of Generative Adversarial Networks(PG-GANs) as an implementation model to generate high-resolution images and to enhance variation of the generated images, and applied it to fashion image data. PG-GANs allows the generator and discriminator to progressively learn at the same time, continuously adding new layers from low-resolution images to result high-resolution images. We also proposed a Mini-batch Discrimination method to increase the diversity of generated data, and proposed a Sliced Wasserstein Distance(SWD) evaluation method instead of the existing MS-SSIM to evaluate the GAN model.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.529-538
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• 2013

Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.65-73
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• 1998

One approach to improved image restoration methods has been the incorporation of additional source information via Gibbs priors that assume a source that is piecewise smooth. A natural Gibbs prior for expressing such constraints is an energy function defined on binary valued line processes as well as source intensities. However, the estimation of both continuous variables and binary variables is known to be a difficult problem. In this work, we consider the application of the deterministic annealing method. Unlike other methods, the deterministic annealing method offers a principled and efficient means of handling the problems associated with mixed continuous and binary variable objectives. The application of the deterministic annealing method results in a sequence of objective functions (defined only on the continuous variables) whose sequence of solutions approaches that of the original mixed variable objective function. The sequence is indexed by a control parameter (the temperature). The energy functions at high temperatures are smooth approximations of the energy functions at lower temperatures. Consequently, it is easier to minimize the energy functions at high temperatures and then track the minimum through the variation of the temperature. This is the essence of a continuation method. We show experimental results, which demonstrate the efficacy of the continuation method applied to a Bayesian restoration model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.3
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• pp.14-24
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• 2007

The purpose of this study was to investigate how the landscape characteristics and the physical factors of landscape would affect the preference for the Gapcheon in Daejeon Metropolitan City. The Gapcheon was divided in three sections of the outskirts, Expopark areas, and residential complexes. After selecting seven landscape points where the sections could be expressed best, photographs were taken both in the upstream and downstream direction. The questionnaire used to evaluate the river's landscape included 20 items of adverbs that described the form of the river and one item to rate the overall preference. By analyzing the 14 pictures taken, the occupancy rates of the landscape elements in terms of the sky, river, vegetation of the river, mountain, and artificial structures. Image factor analysis was conducted for each of the sections in order to analyze the landscape characteristics of the Gapcheon, and then regression analysis was conducted in order to analyze the relationships among the physical factors influencing the preference of the landscapes. The results were as follows : Factors that compose the visual characters of urban river were classified be the aesthetic factor, the emotional factor and the situation factor. These 3 factors showed a 65.8% total variance. The river landscape with the biggest preference was the one from the Daedeok Grand Bridge as the occupancy area of the mountain, sky, and river was large and distributed evenly and the vegetation of the river was in a good harmony with the surroundings. After carrying out regression analysis to examine the relationships between the visual preference of Gapcheon and the physical factors of landscape(the sky, river, vegetation of the river, mountain, and artificial structure), the following regressions model was made : PRE=5.906+0.017(river)-0.053(artificial structure)-0.060(vegetation of the river) (R-square=0.48).