• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.37-41
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• 2003

We have developed a seeing monitoring system and measured seeing variation of the Bohyunsan Optical Astronomy Observatory (BOAO) and the Sobaeksan Optical Astronomy Observatory (SOAO) using a small telescope system. Our seeing monitoring system is similar to the differential image motion monitor (DIMM) installed at the ESO. The ooly difference between the BOAO and the SOAO seeing monitoring system is a detector system, a video camera at the BOAO and ST-4 camera at the SOAO. We confirmed that the seeing monitoring system at the SOAO can measure average seeing size inspite of its simple detector system. From the BOAO seeing measurement, we found that the seeing size changes fast. We expect that our seeing monitoring system could be used for real time seeing monitoring after some improvement, and the data to be obtained would be very useful when we build adaptive optic system in the future.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• Korean Journal of Geomatics
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• v.4 no.1
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• pp.1-8
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• 2004

In the middle-resolution remote sensing, the Ground Sampled Distance (GSD) that the detector senses and samples is generally larger than the actual size of the objects (or materials) of interest, and so several objects are embedded in a single pixel. In this case, as it is impossible to detect these objects by the conventional spatial-based image processing techniques, it has to be carried out at sub-pixel level through spectral properties. In this paper, we explain the sub-pixel analysis algorithm, also known as the Linear Spectral Mixing (LSM) model, which has been experimented using the Hyperion data. To find Endmembers used as the prior knowledge for LSM model, we applied the concept of the convex geometry on the two-dimensional scatter plot. The Atmospheric Correction and Minimum Noise Fraction techniques are presented for the pre-processing of Hyperion data. As LSM model is the simplest approach in sub-pixel analysis, the results of our experiment is not good. But we intend to say that the sub-pixel analysis shows much more information in comparison with the image classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.49-58
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• 2012

Buildings become complex and diverse with time. It is difficult to extract individual buildings using only an optical image, because they have similar spectral characteristics to objects such as vegetation and roads. In this study, we propose a method to extract building area and boundary through integrating airborne Light Detection and Ranging(LiDAR) data and aerial images. Firstly, a binary edge map was generated using Edison edge detector after applying Adaptive dynamic range linear stretching radiometric enhancement algorithm to the aerial image. Secondly, building objects on airborne LiDAR data were extracted from normalized Digital Surface Model and aerial image. Then, a temporary building areas were extracted by overlaying the binary edge map and building objects extracted from LiDAR data. Finally, some building boundaries were additionally refined considering positional accuracy between LiDAR data and aerial image. The proposed method was applied to two experimental sites for validation. Through error matrix, F-measure, Jaccard coefficient, Yule coefficient, and Overall accuracy were calculated, and the values had a higher accuracy than 0.85.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.149-152
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• 2004

A new joint source channel coding reduces both input-width and average current consumption to transmit image data to LCD source drivers. As a source coding, it is based on entropy coding of differential pulse code modulation scheme, especially using median edge detector of image predictor. As a channel coding, it is not a simple pulse amplitude modulation, but linked by source entropy to reduce average amplitude. Simulation results show 1/4 width is achievable by 16-valued transmission with keeping conventional current consumption (0.36 to 1.3).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1677-1684
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• 1996

The theory of optimal stack filtering has been used in difference of estimates(DoE) approach to the detection of intensity edges in noisy image. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates produces the estimated edge map. In this paper, the DoE approach is modified by imposing a symmetry condition of the data used to train the two stack filers. Under this condition, the stack filters obtained are duals of each other. Only one filter must therefore be trained;the other is simply its dual. They also produce statistially unbiased estimates. This new technique is called the symmetric Difference of Estimates (SDoE) approach.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.359-365
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• 2021

GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.31-37
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• 2014

In this paper, to compensate the degraded performance in high-resolution infrared sensor due to assembling error, the influence of each component was evaluated through the sensitivity analysis of lens assembly, axis mirror, and detector and also suggested detector tilt mechanism for compensation. 3 detector tilt mechanisms were investigated. The first one is 'Shim plate' method which is applying shim on installing plane. The second one is 'Tilting screw' method that is using tilt screw for adjusting detection plane. The last one is 'Micrometer head' method that is installing micrometer on detection plane and acquiring quantitative data. Based on the investigation result, 'Tilting screw' method was applied due to ease of user control, small volume, and real-time controllability, thereby we could acquire high-resolution infrared images. The research result shows that the tilting mechanism is necessary technology for the implementation of high-resolution infrared imaging system.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.162-163
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• 1979

A new detector array scheme for the positron camera for tile improved image resolution and a method for the resolution improvement of the undersampled projection data from ring positron camera are proposed. Computer simulation results are presented and problems ana limitations are discussed.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.157-162
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• 2022

Since preclinical positron emission tomography imaging is performed on small animals that are very small compared to the human body, a detector with excellent spatial resolution is required. For this purpose, a system was constructed using a detector using small scintillation pixels. Since the size of the currently developed and used photosensors is limited, excellent spatial resolution can be obtained when the minimum scintillation pixel and maximum array are used. In this study, the size of the photosensor is fixed and various scintillation pixel arrays are configured to match the size of the scintillation pixels, so that no overlap occurs in the flood image and the maximum scintillation pixel array in which all scintillation pixels are distinguished. For this purpose, DETECT2000, which can simulate a detector module composed of a scintillator and an photosensor, was used. A photosensor consisting of a 4 × 4 array of 3 mm × 3 mm pixels was used, and the scintillation pixel array was configured from 8 × 8 to 13 × 13, and simulations were performed. A flood image was constructed using the data obtained from the photosensor pixel, and the maximum scintillation pixel array that does not overlap the image was found through the flood image and the profile. As a result, the size of the scintillation pixel array in which all scintillation pixels are imaged without overlapping each other in the flood image was 11 × 11.