• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.282-296
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• 2012

This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.80-83
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• 1999

An efficient modeling and management of a large amount of surface data for a wide rage of geographic information play an important role in determining the functionality of 3D geographic information system. It has been put many efforts to design and manage an effective way to enhence the manipulation of the data by considering geometry type and data structures. Recently, DEM(Data Elevation Model) and TIN(Triangulated Irregular Network) are used for representing surface data. In this paper, we propose a 3D data processing method. The method utilizes the major properties of DEM and TIN, respectively. Furthermore, by approximating DEM with a TIN of an appropriate resolution, we can support a fast and realistic surface modeling. We implement the structure with the following 4 level stages. The first is an optimal resolution of DEM which represent all of wide range of geographic data. The second is the full resolution DEM which is a subarea of original data generated by user's selection in our implemeatation. The third is the TIN approximation of this data with a proper resolution determined by the relative position with the camera. And the last step is multi-resolution TIN data whose resolution is dynamically decided by considering which direction user take notice currently. Specially, the TIN of the last step is designed for realtime camera navigation. By using the structure we implemented realtime surface clipping, efficient approximation of height field and the locally detailed surface LOD(Level of Detail). We used the initial 10-meter sampling DEM data of Seoul, KOREA and implement the structure to the 3D Virtual GIS based on the Internet.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.157-157
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• 2017

To minimize the damage by wild birds and acquire the benefits such as protection against weeds and maintenance of water content in soil, the mulching black color vinyl after seeding should be carried out. Non-contact and non-destructive methods that can continuously determine the locations are necessary. In this study, a crop position detection method was studied that uses infrared thermal image sensor to determine the cotyledon position under vinyl mulch. The moving system for acquiring image arrays has been developed for continuously detecting crop locations under plastic mulching on the field. A sliding mechanical device was developed to move the sensor, which were arranged in the form of a linear array, perpendicular to the array using a micro-controller integrated with a stepping motor. The experiments were conducted while moving 4.00 cm/s speed of the IR sensor by the rotational speed of the stepping motor based on a digital pulse width modulation signal from the micro-controller. The acquired images were calibrated with the spatial image correlation. The collected data were processed using moving averaging on interpolation to determine the frame where the variance was the smallest in resolution units of 1.02 cm. Non-linear integral interpolation was one of method for analyzing the frequency using the normalization image and then arbitrarily increasing the limited data value of $16{\times}4pixels$ in one frame. It was a method to relatively reduce the size of overlapping pixels by arbitrarily increasing the limited data value. The splitted frames into 0.1 units instead of 1 pixel can propose more than 10 times more accurate and original method than the existing correction method. The non-integral calibration method was conducted by applying the subdivision method to the pixels to find the optimal correction resolution based on the first reversed frequency. In order to find a correct resolution, the expected location of the first crop was indicated on near pixel 4 in the inversion frequency. For the most optimized resolution, the pixel was divided by 0.4 pixel instead of one pixel to find out where the lowest frequency exists.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.66-71
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• 1999

For given 3D geographic data which is usually of DEM(Data Elevation Model) format, we have to represent and manipulate the data in various ways. For example, we have to draw a part of them in drawing canvas. To do this we give users a way of selecting area they want to visualize. And we have to give a base tool for users to select the local area which can be chosen for some geographic operation. In this paper, we propose a 3D data processing method for representation and manipulation. The method utilizes the major properties of DEM and TIN(Triangular Irregular Network), respectively. Furthermore, by approximating DEM with a TIN of an appropriate resolution, we can support a fast and realistic surface modeling. We implement the structure with the following 4 level stages. The first is an optimal resolution of DEM which represent all of wide range of geographic data. The second is the full resolution DEM which is a subarea of original data generated by user's selection in our implemeatation. The third is the TIN approximation of this data with a proper resolution determined by the relative position with the camera. And the last step is multi-resolution TIN data whose resolution is dynamically decided by considering which direction user take notice currently. Specialty, the TIN of the last step is designed for realtime camera navigation. By using the structure we implemented realtime surface clipping, efficient approximation of height field and the locally detailed surface LOD(Level of Detail). We used the initial 10-meter sampling DEM data of Seoul, KOREA and implement the structure to the 3D Virtual GIS based on the Internet.

• Journal of radiological science and technology
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• v.22 no.1
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• pp.5-11
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• 1999

This paper reviews recent major activities on instrumentation and methodology of PET. The performance of the PET instrumentation can be expressed by four physical characteristics, 1) spatial resolution, 2) coincidence resolving time, 3) energy resolution, and 4) detection efficiency. The physical and technical aspects of PET systems are briefly discussed along with these characteristics. Toward high resolution PET the recent trend has been to design multiple rings of densely packed detector arrays with scintillators. In order to satisfy the sampling requirement in reconstruction, continuous detector units has been developed. Iterative image reconstruction algorithms have received considerable attention for improvement of both the sampling requirement and image quality toward the stationary PET. Better resolving time improves the maximum true coincidence rate, which is also increased with more detectors placed in coincidence with each other. It suggests that volume PET is promising for enhancement of detection efficiency. The scattered coincidence event rate may be reduced by using detectors with better energy resolution. The use of interplane septa, however, takes over improvement of energy resolution in 2D PET. Energy resolution becomes an important factor for image quality under the condition of septa removal such as volume PET. Toward full utilization of emitting photons, 3D reconstruction incorporating oblique rays has been studied, and volume reconstruction algorithms have been developed. Practical volume PET systems impose heavy burden not only to detector sets and coincidence circuits, but also to computers in the memory requirements and the data processing. In conclusion, there have been many ingenious methods in development of PET instrumentation, which are based on unique capability of PET. They will be expected to overcome technical limitations, and to approach the fundamental limits.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.273-279
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• 2013

The purpose of the study was to present basic data to evaluation of the spatial resolution for exposure class(EC) in computed radiography(CR) by using the modulation transfer function(MTF). In this study, MTF was measured the edge method by using image plate(IP) of $100{\mu}mm$ pixels. A standard beam quality RQA5 based on an international electro-technical commission(IEC) standard was used to perform the X-ray imaging studies. Digital imaging began to set the sensitivity to EC 50, 100, 200, 300, 400, 600, 800, 1200 in X-ray irradiated to IP. The MTF 50% and 10% in the final images was analysis by using an authorized image analysis program the Origin 8.0 and the image J. As a results, the EC 200 was the best spatial resolution at MTF 50% ($1.979{\pm}0.114lp/mm$) and MTF 10% ($3.932{\pm}0.041$). Therefore, the EC 200 could be useful for the diagnosis of diseases that require high spatial resolution such as fractures.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.421-430
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• 2010

Image segmentation technique is becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification to extract object regions of interest within images. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Improved Seeded Region Growing (ISRG) and Region merging. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained multi-spectral edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying ISRG to consider spectral and edge information. Finally the region merging process, integrating region texture and spectral information, was carried out to get the final segmentation result. The accuracy assesment was done using the unsupervised objective evaluation method for evaluating the effectiveness of the proposed method. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.3
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• pp.180-190
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• 2017

This paper describes the application of Multi-frame based super-resolution method to enhance resolution of image information from the UAV, and the improvement of UAV's ground target recognition ability. To verify this algorithm, we designed a flight/ground control system, and the UAV, and then the algorithm was validated using the UAV system with ground target. As a result of the comparison between the pre-applied image and post-applied one shows that the RMSE is from 0.0677 to 0.0315, NRMSE is from 7.4030% to 3.5726%, PSNR is from 23.3885dB to 30.0036dB, and SSIM is from 0.6996 to 0.8948. Through these results, we validate this study can enhance the resolution of UAV's image using Multi-frame based super-resolution algorithm.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.71-84
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• 2001

The geographical phenomena in space are well observed in the specific scale. This scale is called the operational scale. For an analysis of the optimum scale, it is needed to measure and represent the characteristics of attribute information extracted from the satellite imagery. The development of remote sensing technique makes various images with different resolution available. Researchers can select the image with optimum resolution for their analysis among various resolutions. For an effective analysis of the scale characteristics of satellite image, we investigated the characteristics of attribute information extracted from satellite image with different resolution. The two stage-procedure for exploring the optimum resolution proposed in this study was tested by applying to the satellite imagery covering Sunchon bay. This procedure can be an effective tool utilizing the scale characteristics of attribute information extracted from satellite imagery.

• Journal of Digital Policy
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• v.3 no.3
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• pp.9-14
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• 2024

In this paper, proposes a method using a multi block structure composed of residual blocks with adaptive weights to improve the quality of results in single image super resolution. In the process of generating super resolution images using deep learning, the most critical factor for enhancing quality is feature extraction and application. While extracting various features is essential for restoring fine details that have been lost due to low resolution, issues such as increased network depth and complexity pose challenges in practical implementation. Therefore, the feature extraction process was structured efficiently, and the application process was improved to enhance quality. To achieve this, a multi block structure was designed after the initial feature extraction, with nested residual blocks inside each block, where adaptive weights were applied. Additionally, for final high resolution reconstruction, a multi kernel image reconstruction process was employed, further improving the quality of the results. The performance of the proposed method was evaluated by calculating PSNR and SSIM values compared to the original image, and its superiority was demonstrated through comparisons with existing algorithms.