• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1120-1128
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• 2022

In the event of a marine accident, the longer the exposure time to the sea increases, the faster the chance of survival decreases. However, because the search area of the sea is extremely wide compared to that of land, marine object detection technology based on the sensor mounted on a satellite or an aircraft must be applied rather than ship for an efficient search. The purpose of this study was to rapidly detect an object in the ocean using a hyperspectral image sensor mounted on an aircraft. The image captured by this sensor has a spatial resolution of 8,241 × 1,024, and is a large-capacity data comprising 127 spectra and a resolution of 0.7 m per pixel. In this study, a marine object detection model was developed that combines a seawater identification algorithm using DBSCAN and a density-based land removal algorithm to rapidly analyze large data. When the developed detection model was applied to the hyperspectral image, the performance of analyzing a sea area of about 5 km² within 100 s was confirmed. In addition, to evaluate the detection accuracy of the developed model, hyperspectral images of the Mokpo, Gunsan, and Yeosu regions were taken using an aircraft. As a result, ships in the experimental image could be detected with an accuracy of 90 %. The technology developed in this study is expected to be utilized as important information to support the search and rescue activities of small ships and human life.

• Design Convergence Study
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• v.15 no.5
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• pp.71-83
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• 2016

Interior panels are usually used in finishing of interior walls for not only decorative effects but also information transfer. According to designer's design placing interior panels may need repetitive tasks and the emphasis of this paper is to support an automation of these tasks. Considering the utilization characteristics of interior panels, we propose three method to present patterns by using bitmap image pixels and interior panels' shape changes, based on the theoretical consideration. In addition, in order to approve the possibility of the proposed methods, we have implemented the BIM based interior panels auto layout tool which applied one of the three methods to present patterns by using bitmap image pixel values and panel identification attributes. This tool also supports auto generation of quantity and panel arrangement sequence information that will be used in future construction phase. We expect that this approach will also be used in other decorative objects which require repetition of the basic units, such as floor tiles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.75-88
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• 2009

This paper presents a video quality assessment method based on quality degradation factors of real-time multimedia streaming services. The video quality degradation is caused by video source compression and network states. In this paper, we propose a blocky metric on an image domain to measure quality degradation by video compression. In this paper, the proposed boundary strength index for the blocky metric is defined by ratio of the variation of two pixel values adjacent to $8{\times}8$ block boundary and the average variation at several pixels adjacent to the two boundary pixels. On the other hand, unnatural image movement caused by network performance deterioration such as jitter and delay factors can be observed. In this paper, a temporal-Jerkiness measurement method is proposed by computing statistics of luminance differences between consecutive frames and play-time intervals between frames. The proposed final Perceptual Video Quality Metric (PVQM) is proposed by consolidating both blocking strength and temporal-jerkiness. To evaluate performance of the proposed algorithm, the accuracy of the proposed algorithm is compared with Difference of Mean Opinion Score (DMOS) based on human visual system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.79-89
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• 2010

Recently, distributed video coding (DVC) has been actively studied for low complexity video encoder. The complexity of the encoder in DVC is much simpler than that of traditional video coding schemes such as H.264/AVC, but the complexity of the decoder in DVC increases. In this paper, we propose the Region-Of-Interest (ROI) based DVC with low decoding complexity. The proposed scheme uses the ROI, the region the motion of objects is quickly moving as the input of the Wyner-Ziv (WZ) encoder instead of the whole WZ frame. In this case, the complexity of encoder and decoder is reduced, and the bite rate decreases. Experimental results show that the proposed scheme obtain 0.95 dB as the maximum PSNR gain in Hall Monitor sequence and 1.87 dB in Salesman sequence. Moreover, the complexity of encoder and decoder in the proposed scheme is significantly reduced by 73.7% and 63.3% over the traditional DVC scheme, respectively. In addition, we employ the layered belief propagation (LBP) algorithm whose decoding convergence speed is 1.73 times faster than belief propagation algorithm as the Low-Density Parity-Check (LDPC) decoder for low decoding complexity.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.163-171
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• 2003

To evaluate the performance of the digital radiography(DR) system developed in our group, the modulation transfer function(MTF) was measured and compared with that of an analog X- ray detector, film/screen system. The DR system has an amorphous selenium(a-Se) layer vacuum-evaporated on a TFT flat panel detector. The speed class 400 film/screen (Fuji) system has been being used in the clinical field as analog X-ray detectors. Both the square wave and slit method were used to evaluate their MTF. The square method was applied to both film/screen and the DR system. The slit method, however, was applied to only DR system. The full-width half maximum resolution of film/screen was 357${\mu}{\textrm}{m}$(1.4 lp/mm at 50% spatial frequency), and the resolution of DR was limited to 200${\mu}{\textrm}{m}$(2.5 lp/mm at 30%). These results indicate the measured resolution limitations approximate to the pixel pitch, 139 ${\mu}{\textrm}{m}$ of TFT. The MTF of DR is higher than that of film/screen by the factor of 1.785. It is proved that our a-Se based DR system has potential usefulness in the clinical field.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.623-629
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• 2002

In transmitting compressed video bit-stream over Internet, packet losses cause error propagations in both spatial and temporal domains, which in turn leads to severe degradation I image quality. In this paper, a new error concealment algorithm, called EBMA(Edge Detection based Boundary Matching Algorithm), is proposed to repair damaged portions of the video frames in the receiver. Conventional BMA(Boundary Matching Algorithm) assumes that the pixels on the boundary of the missing block and its neighboring blocks are very similar, but has no consideration of edges across the boundary. In our approach, the edges are detected across the boundary of the lost or erroneous block. Once the orientation of each edge is found, only the pixel difference along the expected edges across the boundary is measured instead of the calculation of difference along the expected edges across the boundary is measured instead of the calculation of differences between all adjacent pixels on the boundary Therefore, the proposed approach needs very few computations and the experiment shows and improvement of the performance over the conventional BMA in terms of both subjective and objective quality of video sequences.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1061-1073
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• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.179-197
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• 2020

Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.