• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.395-407
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• 2023

Super-resolution (SR) has great significance in image processing because it enables downstream vision tasks with high spatial resolution. Recently, SR studies have adopted deep learning networks and achieved remarkable SR performance compared to conventional example-based methods. Deep-learning-based SR models generally require low-resolution (LR) images and the corresponding high-resolution (HR) images as training dataset. Due to the difficulties in obtaining real-world LR-HR datasets, most SR models have used only HR images and generated LR images with predefined degradation such as bicubic downsampling. However, SR models trained on simple image degradation do not reflect the properties of the images and often result in deteriorated SR qualities when applied to real-world images. In this study, we propose an image degradation model for HR satellite images based on the modulation transfer function (MTF) of an imaging sensor. Because the proposed method determines the image degradation based on the sensor properties, it is more suitable for training SR models on remote sensing images. Experimental results on HR satellite image datasets demonstrated the effectiveness of applying MTF-based filters to construct a more realistic LR-HR training dataset.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.1-10
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• 2017

An UAV (Unmanned Aerial Vehicle) is a flight system that is designed to conduct missions without a pilot. Compared to traditional airborne-based photogrammetry, UAV-based photogrammetry is inexpensive and can obtain high-spatial resolution data quickly. In this study, we aimed to classify the land cover using high-spatial resolution images obtained using a UAV. An RGB camera was used to obtain high-spatial resolution orthoimage. For accurate classification, multispectral image about same areas were obtained using a multispectral sensor. A DSM (Digital Surface Model) and a modified NDVI (Normalized Difference Vegetation Index) were generated using images obtained using the RGB camera and multispectral sensor. Pixel-based classification was performed for twelve classes by using the RF (Random Forest) method. The classification accuracy was evaluated based on the error matrix, and it was confirmed that the proposed method effectively classified the area compared to supervised classification using only the RGB image.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.255-258
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• 2006

With the increasing availability of high-resolution satellite imagery, the demand for ortho-rectified products will also be growing. High-resolution of the imagery (up to 1m) the desired accuracy of the ortho-rectification is more sensitive to a number of factors. including satellite position, velocity, internal sensor error (specifically, misalignment. lens distortion, etc.). sensor modeling, relief displacement and matching error, etc. The main objective of this study is to analysis the accuracy of high resolution satellite data using simulation data.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.856-859
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• 2002

A system for high-resolution analysis of defective elementary cell (R, G or B) on Flat Panel Display (FPD) is described. Based on multiple acquisitions of low-resolution shifted images of the display, our system doesn't require a high-resolution sensor neither tedious alignment of the display, and will remain up to date even facing an important increase of the display dimensions. Our process, highly automated and thus flexible and robust, is expected to perform a full analysis in less than 60s. It is mainly intended for production tests and display classification by manufacturers.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.103-109
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• 2007

Ortho images and Digital Elevation Model (DEM) have been applied in various fields. It is necessary to acquire Ground Control Points (GCPs) for processing high resolution satellite images. However surveying GCPs require many time and expense. This study was performed to investigate whether GCPs automatically extracted from ortho images and DTED Level 2 can be applied to sensor modeling for high resolution satellite images. We analyzed the performance of the sensor model established by GCPs extracted automatically. We acquired GCPs by matching satellite image against ortho images. We included the height acquired from DTED Level 2 data in these GCPs. The spatial resolution of the DTED Level 2 data is about 30m. Absolution accuracy of this data is below 18m above MSL. The spatial resolution of ortho image is 1m. We established sensor model from IKONOS images using GCPs extracted automatically and generated DEMs from the images. The accuracy of sensor modeling is about $4{\sim}5$ pixel. We also established sensor models using GCPs acquired based on GPS surveying and generated DEMs. Two DEMs were similar. The RMSE of height from the DEM by automatic GCPs and DTED Level 2 is about 9 m. So we think that GCPs by DTED Level 2 and ortho image can use for IKONOS sensor modeling.

• Journal of Sensor Science and Technology
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• v.26 no.5
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• pp.348-352
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• 2017

In this paper, we propose a high resolution A/D converter for a sensor interface that processes low frequency AC signals. A 6b SAR ADC with low power consumption and a 11b incremental ADC with high resolution are combined together to perform 15b resolution. Conventional hybrid ADC has a disadvantage that it can convert t only DC signal, but in this paper, it is possible to convert data to AC signal by increasing input range of incremental ADC. The decimation filter is implemented on-chip. The designed Hybrid ADC operates at supply voltage of 1.8V and consumes the current of 6.98uA. The OSR (oversampling ratio) is 90. And SFDR, SNDR, ENOB and FoMs are 96.59dB, 88.47dB, 14.4-bit and 139.5dB, respectively.

• Journal of information and communication convergence engineering
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• v.13 no.1
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• pp.21-26
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• 2015

A wireless sensor network (WSN) is designed and implemented for a freeze dryer. Freeze-drying technology is widely used in the fields of pharmacy and biotechnology as well as the food and agriculture industries. Taking into account the demand for high-resolution pressure and temperature measurements in a freeze dryer, the proposed WSN has a significant advantage of creating a monitoring environment in a freeze dryer. The proposed WSN uses a ZigBee/IEEE 802.15.4 network with an altimeter module that contains a high-resolution pressure and temperature sensor with a serial digital data interface. The ZigBee network is suitable for low-energy and low-data-rate applications in the field of wireless communication. The altimeter module is capable of sensing pressure in the range of 7.5-975 Torr (10-1300 mbar) and temperature in the range of $-40^{\circ}C$ to $125^{\circ}C$ with a DC power consumption of $3{\mu}W$. The implemented WSN is installed in a commercial laboratory freeze dryer in order to demonstrate its functionality and efficiency. A comparison with the temperature profile measured by a thermocouple installed in the freeze dryer reveals that the resolution of the temperature profile measured by WSN is superior to that measured by the thermocouple.

• Smart Structures and Systems
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• v.16 no.4
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• pp.683-699
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• 2015

Time Domain Reflectometry (TDR) has been extensively applied for various laboratory and field studies. Numerous different TDR probes are currently available for measuring soil moisture content and detecting interfaces (i.e., due to landslides or structural failure). This paper describes the development of an innovative spiral-shaped TDR probe that features much higher sensitivity and resolution in detecting interfaces than existing ones. Finite element method (FEM) simulations were conducted to assist the optimization of sensor design. The influence of factors such as wire interval spacing and wire diameter on the sensitivity of the spiral TDR probe were analyzed. A spiral TDR probe was fabricated based on the results of computer-assisted design. A laboratory experimental program was implemented to evaluate its performance. The results show that the spiral TDR sensor featured excellent performance in accurately detecting thin water level variations with high resolution, to the thickness as small as 0.06 cm. Compared with conventional straight TDR probe, the spiral TDR probe has 8 times the resolution in detecting the water level changes. It also achieved 3 times the sensitivity of straight TDR probe.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.298-302
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• 2012

The linear encoder used in the BLAC driving circuit consists usually analog type sensor, and need signal transform from analog sinusoidal to digital one for application in the PWM algorithm that is used to control motor current. When the motor is driven in low speed, it is required many operations and higher quality DSP to convert the hole sensor signal to digital one with enough resolution. In this paper, the another method to convert that signal with enough resolution without calculation of sine function is proposed. This is very simple and have high resolution even if the motor is driving in low speed. To verify the proposed method, BLAC motor is used, and it is proved that the motor is tracking well the reference step signal in the low speed as well as in the high one.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.280-284
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• 2016

For an arc-flash protection system, the selection of arc-flash sensor in implementation is largely dependent on the coverage area and the spatial resolution. Typically, a point sensor is used to accurately measure an arc event within a very narrow region; whereas, a loop or a line sensor can cover several electrical compartment at the same time, but with a poor resolution. In this work, a novel scheme for an arc-flash sensor was developed by making use of the transmission loss of plastic optical fibers (POFs) to cover a broad range with a high spatial resolution. By relating the amplitude ratio of the arc-signals at the ends of the POF with the arc-location, arc events could be located with a resolution of ~5 cm within a spatial range of 10 m, which has not been reported yet.