• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.773-775
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• 2003

From the view point of data fusion, we integrate LIDAR data and digital aerial images to perform 3D building modeling in this study. The proposed scheme comprises two major parts: (1) building block extraction and (2) building model reconstruction. In the first step, height differences are analyzed to detect the above ground areas. Color analysis is then performed for the exclusion of tree areas. Potential building blocks are selected first followed by the refinement of building areas. In the second step, through edge detection and extracting the height information from LIDAR data, accurate 3D edges in object space is calculated. The accurate 3D edges are combined with the already developed SMS method for building modeling. LIDAR data acquired by Leica ALS 40 in Hsin-Chu Science-based Industrial Park of north Taiwan will be used in the test.

• Korean Journal of Radiology
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• v.20 no.5
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• pp.729-738
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• 2019

Objective: To assess the effects of iterative model reconstruction (IMR) on image quality for demonstrating non-calcific high-risk plaque characteristics of coronary arteries. Materials and Methods: This study included 66 patients (53 men and 13 women; aged 39-76 years; mean age, 55 ± 13 years) having single-vessel disease with predominantly non-calcified plaques evaluated using prospective electrocardiogram-gated 256-slice CT angiography. Paired image sets were created using two types of reconstruction: hybrid iterative reconstruction (HIR) and IMR. Plaque characteristics were compared using the two algorithms. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images and the CNR between the plaque and adjacent adipose tissue were also compared between the two reformatted methods. Results: Seventy-seven predominantly non-calcified plaques were detected. Forty plaques showed napkin-ring sign with the IMR reformatted method, while nineteen plaques demonstrated napkin-ring sign with HIR. There was no statistically significant difference in the presentation of positive remodeling, low attenuation plaque, and spotty calcification between the HIR and IMR reconstructed methods (all p > 0.5); however, there was a statistically significant difference in the ability to discern the napkin-ring sign between the two algorithms (χ² = 12.12, p < 0.001). The image noise of IMR was lower than that of HIR (10 ± 2 HU versus 12 ± 2 HU; p < 0.01), and the SNR and CNR of the images and the CNR between plaques and surrounding adipose tissues on IMR were better than those on HIR (p < 0.01). Conclusion: IMR can significantly improve image quality compared with HIR for the demonstration of coronary artery and atherosclerotic plaques using a 256-slice CT.

• Journal of radiological science and technology
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• v.35 no.4
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• pp.353-360
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• 2012

Diverse designs of collimator have been applied to Single Photon Emission Computed Tomography (SPECT) according to the purpose of acquisition; thus, it is necessary to reflect geometric characteristic of each collimator for successive image reconstruction. This study carry out reconstruction algorithm for imaging system in nuclear medicine with pinhole collimator. Especially, we study to solve sampling problem which caused in the system model of pinhole collimator. System model for a maximum likelihood expectation maximization (MLEM) was developed based on the geometry of the collimator. The projector and back-projector were separately implemented based on the ray-driven and voxel-driven methods, respectively, to overcome sparse sampling problem. We perform phantom study for pinhole collimator by using geant4 application for tomographic emission(GATE) simulation tool. The reconstructed images show promising results. Designed iterative reconstruction algorithm with unmatched system model effective to remove sampling problem artefact. Proposed algorithm can be used not only for pinhole collimator but also for various collimator system of imaging system in nuclear medicine.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.973-988
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• 2009

The objective of this study is to develop an accurate and robust two-dimensional finite element method to simulate drying and wetting in complex natural rivers. The Dry/Wet algorithm developed in this study is Grid Reconstruction Method which requires the definition of new meshes and renumbering of the nodes. Any drop of water level in the two-dimensional domain results in eliminating nodes and elements. Several numerical simulations were carried out to examine the performance of the Grid Reconstruction Method for the purpose of validation and verification of the model. The accuracy and application of the developed model are verified by comparing simulated results with observed values.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.537-543
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• 2004

In order to create three-dimensional model for human body, a method that reconstructs geometric models from contour lines on cross-section images is commonly used. We can get a set of contour lines by acquiring CT or MR images and segmenting anatomical structures. Previously proposed method divides entire contour line into simply matched regions and clefts. Since long processing time is required for reconstructing cleft regions, its performance might be degraded when manipulating complex data such as cross-sections for human body. In this paper, we propose a fast reconstruction method. It generates a triangle strip with single tiling operation for simple region that does not contain branch structures. If there exist branches in contour lines, it partitions the contour line into several sub-contours by considering the number of vertices and their spatial distribution. We implemented an automatic surface reconstruction system by using our method which reconstructs three-dimensional models for anatomical structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.991-996
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• 2007

Recently, a computational reconstruction method using an integral imaging technique, which is a promise three-dimensional display technique, has been actively researched. This method is that 3-D images can be digitally reconstructed at the required output planes by superposition of all of the inversely enlarged elemental images by using a hypothetical pinhole array model. However, the conventional method mostly yields reconstructed images having a low-resolution, because there are some intensity irregularities with a grid structure at the reconstructed mage plane by using square-type elemental images. In this paper, to overcome this problem, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIR method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resolution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.989-1004
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• 2009

The objective of this study is to examine validation of Grid Reconstruction Method, which is developed to simulate drying/wetting in complex natural rivers with wetting and drying domain areas. To verify application of the developed model, the model was applied to natural rivers with wetting and drying domain areas such as Han river and Nakdong river. The simulation results have shown good agreements with observed data and the results for the developed model were more accurate and improved stability of numerical computation than those of RMA-2 model. If the analysis of contaminant advection-diffusion and sediment transport are performed with the study results, the results can be effectively applied to river flow analysis and ecological hydraulics.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1157-1160
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• 2005

The denoising and reconstruction of color images are increasingly studied in the field of computer vision and image processing. Especially, the denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noises on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps; training of canonical eigenface space using PCA, automatic extracting of face features using active appearance model, relighing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denosing method efficiently removes complex color noises on input face images.