• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.999-1011
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• 2021

In spatio-temporal fusion aiming at predicting images with both high spatial and temporal resolutionsfrom multi-sensor images, the radiometric inconsistency between input multi-sensor images may affect prediction performance. This study investigates the effect of radiometric correction, which compensate different spectral responses of multi-sensor satellite images, on the spatio-temporal fusion results. The effect of relative radiometric correction of input images was quantitatively analyzed through the case studies using Sentinel-2, PlanetScope, and RapidEye images obtained from two croplands. Prediction performance was improved when radiometrically corrected multi-sensor images were used asinput. In particular, the improvement in prediction performance wassubstantial when the correlation between input images was relatively low. Prediction performance could be improved by transforming multi-sensor images with different spectral responses into images with similar spectral responses and high correlation. These results indicate that radiometric correction is required to improve prediction performance in spatio-temporal fusion of multi-sensor satellite images with low correlation.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.329-339
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• 2003

In this study, an approach of image fusion in decision level has been proposed for unsupervised image classification using the images acquired from multiple sensors with different characteristics. The proposed method applies separately for each sensor the unsupervised image classification scheme based on spatial region growing segmentation, which makes use of hierarchical clustering, and computes iteratively the maximum likelihood estimates of fuzzy class vectors for the segmented regions by EM(expected maximization) algorithm. The fuzzy class vector is considered as an indicator vector whose elements represent the probabilities that the region belongs to the classes existed. Then, it combines the classification results of each sensor using the fuzzy class vectors. This approach does not require such a high precision in spatial coregistration between the images of different sensors as the image fusion scheme of pixel level does. In this study, the proposed method has been applied to multispectral SPOT and AIRSAR data observed over north-eastern area of Jeollabuk-do, and the experimental results show that it provides more correct information for the classification than the scheme using an augmented vector technique, which is the most conventional approach of image fusion in pixel level.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.88-95
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• 2005

Direct Georeferencing by combined multi-sensor based on the direct measurement of the projection centers and rotation angle of sensor through loading the GPS and INS in aircraft. The method of combined multi-sensor can offer us to acquire the exterior orientation parameters with only minimum GCPs, even the ground control process could be completely skipped. Consequently, It is possible extreme to reduce the time and expense for the mapping process. In this study, a CCD camera is simultaneously used in combined multi-sensor surveying, and acquired CCD image through Direct Georeferencing produce digital orthoimage. In this process, methods of combining sensor and digital orthoimage are examined and estimated. For the comparison of the positioning accuracy digital orthoimage through Direct Georeferencing, GCPs determined by GPS surveying are used. Two digital orthoimage are produced; one with a few GCP and the other without them. The accuracy of orthoimages produced through combined multi-sensor with GCPs meets that of 1:1,000 maps. Without GCPs, it meets that of 1:5,000 maps.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.359-362
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• 2001

본 논문에서는 광학센서와 적외선 센서를 사용하는 Multi-sensor 시스템에서 영상 정보를 통한 물체의 추적 및 인식에 필요한 영상을 분리하는데 필요한 전처리와 object 기반의 추적 방법을 제안하였다. 일반적인 추적 알고리즘의 목표는 consistency를 유지하는데 있다. 그러나 인식에 필요한 영상을 분리하기 위해서는 물체의 범위를 정확히 판단 할 수 있는 능력이 중요하다. 이를 위해 CCD와 IR영상에 동시에 적용 가능한 전처리 기법과 object 기반의 two-step 추적 알고리즘을 통해 consistency외에도, 물체의 범위를 estimation하여 인식에 필요한 범위를 분리해 낸다. 본 논문에서는 ITS 의 ETCS application을 위해 이종 센서인 CCD와 IR의 야간 차량 영상정보를 이용하여 알고리즘을 test 하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.81-88
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• 2015

Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.41-48
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• 2012

Using multi-sensor or multi-temporal high resolution satellite images together is essential for efficient applications in remote sensing area. The purpose of this paper is to estimate geometric difference of translations between high-resolution optical and SAR images automatically. The geometric and radiometric pre-processing steps were fulfilled to calculate the similarity between optical and SAR images by using Mutual Information method. The coarsest-level pyramid images of each sensor constructed by gaussian pyramid method were generated to estimate the initial translation difference of the x, y directions for calculation efficiency. The precise geometric difference of translations was able to be estimated by applying this method from coarsest-level pyramid image to original image in order. Yet even when considered only translation between optical and SAR images, the proposed method showed RMSE lower than 5m in all study sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.30-31
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• 2020

일반적으로 CCTV 녹화기는 24시간 중단없이 다중 카메라로 부터 수신되는 Video, Audio, Meta 데이터를 파일형태로 저장한다. 그리고 다양한 IoT 센서들은 사건(event)이 발생되었을 때, 입력되는 데이터를 기록한다. 그런데 이 형태의 데이터를 통합하여 사용하는 서비스들에 대한 요구가 증대되고 있다. 그런데 영상데이터와 IoT센서 데이터를 분리해 저장하고 관리하는 기존의 방식으로는 사용 센서의 개수 등에 따라 물리적인 크기가 커지고 관리의 복잡성이 커지는 문제가 발생한다. 본 논문에서는 다중 카메라로부터 입력되는 동영상 데이터와 IoT 센서 데이터를 통합하여 저장하는 방안을 제시한다. 이러한 통합 데이터의 고속 입출력을 지원하기 위해, 본 연구에서는 자체 파일시스템을 개발하였고 저장되는 각각의 파일을 mp4 표준을 따르게 하여 호환성을 보장하도록 구현하였다. 그래서 동영상 파일 포맷으로 널리 사용되는 MP4 포맷에 IoT센서 데이터를 함께 저장함으로써 동영상과 IoT센서의 정보를 효율적으로 관리하고 검색의 편의성을 높일 수 있게 되었다.

• 한국IT서비스학회:학술대회논문집
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• 2010.05a
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• pp.207-210
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• 2010

무선 센서 네트워크 시스템을 이용한 많은 응용 시스템이 연구되고 있는 가운데, 최근 무선 센서 네트워크 시스템의 신뢰성 확보에 대한 문제점이 대두되었다. 이러한 문제점을 해결하기 위하여 영상 데이터를 전송함으로써 보다 신뢰성 있는 정보를 제공할 수 있는 멀티미디어 센서 네트워크에 대한 연구가 활발히 진행되고 있다. 그러나 영상 데이터를 저속의 멀티 홉 무선 센서 네트워크 환경에서 효율적으로 전송하는 프로토콜에 관련된 연구는 비교적 많지 않다. 지금까지의 통신 프로토콜들은 비교적 단순한 센싱 데이터를 전송할 수 있도록 설계되었으며, 새로운 응용들을 지원하기 위해서는 새로운 통신 프로토콜이 필요하다. 따라서 본 논문에서는 연속적인 영상 데이터를 멀티 홉 환경에서 효율적으로 전송할 수 있는 다중 경로 간 간섭이 없는 간섭 회피 다중 경로 설정 기법을 제안한다.