• 제목/요약/키워드: remote sensing image

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Wavelet Algorithms for Remote Sensing

  • CHAE Gee Ju;CHOI Kyoung Ho
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.224-227
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    • 2004
  • From 1980's, the DWT(Discrete Wavelet Transform) is applied to the data/image processing. Many people use the DWT in remote sensing for diversity purposes and they are satisfied with the wavelet theory. Though the algorithm for wavelet is very diverse, many people use the standard wavelet such as Daubechies D4 wavelet and biorthogonal 9/7 wavelet. We will overview the wavelet theory for discrete form which can be applied to the image processing. First, we will introduce the basic DWT algorithm and review the wavelet algorithm: EZW (Embedded Zerotree Wavelet), SPIHT(Set Partitioning in Hierarchical Trees), Lifting scheme, Curvelet, etc. Finally, we will suggest the properties of wavelet algorithm; and wavelet filter for each image processing in remote sensing.

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PARALLAX ADJUSTMENT FOR REALISTIC 3D STEREO VIEWING OF A SINGLE REMOTE SENSING IMAGE

  • Kim, Hye-Jin;Choi, Jae-Wan;Chang, An-Jin;Yu, Ki-Yun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.452-455
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    • 2007
  • 3D stereoscopic viewing of large scale imagery, such as aerial photography and satellite images, needs different parallaxes relative to the display scale. For example, when a viewer sees a stereoscopic image of aerial photography, the optimal parallax of its zoom-in image should be smaller than that of its zoom-out. Therefore, relative parallax adjustment according to the display scale is required. Merely adjusting the spacing between stereo images is not appropriate because the depths of the whole image are either exaggerated or reduced entirely. This paper focuses on the improving stereoscopic viewing with a single remote sensing image and a digital surface model (DSM). We present the parallax adjustment technique to maximize the 3D realistic effect and the visual comfort. For remote sensing data, DSM height value can be regarded as disparity. There are two possible kinds of methods to adjust the relative parallax with a single image performance. One is the DSM compression technique: the other is an adjustment of the distance between the original image and its stereo-mate. In our approach, we carried out a test to evaluate the optimal distance between a single remote sensing image and its stereo-mate, relative to the viewing scale. Several synthetic stereo-mates according to certain viewing scale were created using a parallel projection model and their anaglyphs were estimated visually. The occlusion of the synthetic stereo-mate was restored by the inpainting method using the fields of experts (FoE) model. With the experiments using QuickBird imagery, we could obtain stereoscopic images with optimized parallax at varied display scales.

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Optimizing Image Size of Convolutional Neural Networks for Producing Remote Sensing-based Thematic Map

  • Jo, Hyun-Woo;Kim, Ji-Won;Lim, Chul-Hee;Song, Chol-Ho;Lee, Woo-Kyun
    • 대한원격탐사학회지
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    • 제34권4호
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    • pp.661-670
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    • 2018
  • This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method

  • Bian, Yan;Gong, Yusheng;Ma, Guopeng;Duan, Ting
    • Journal of Information Processing Systems
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    • 제17권5호
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    • pp.947-959
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    • 2021
  • Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GA-OTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.

THE DEVELOPMENT OF CIRCULARLY POLARIZED SYNTHETIC APERTURE RADAR SENSOR MOUNTED ON UNMANNED AERIAL VEHICLE

  • Baharuddin, Merna;Akbar, Prilando Rizki;Sumantyo, Josaphat Tetuko Sri;Kuze, Hiroaki
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.441-444
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    • 2008
  • This paper describes the development of a circularly polarized microstrip antenna, as a part of the Circularly Polarized Synthetic Aperture Radar (CP-SAR) sensor which is currently under developed at the Microwave Remote Sensing Laboratory (MRSL) in Chiba University. CP-SAR is a new type of sensor developed for the purpose of remote sensing. With this sensor, lower-noise data/image will be obtained due to the absence of depolarization problems from propagation encounter in linearly polarized synthetic aperture radar. As well the data/images obtained will be investigated as the Axial Ratio Image (ARI), which is a new data that hopefully will reveal unique various backscattering characteristics. The sensor will be mounted on an Unmanned Aerial Vehicle (UAV) which will be aimed for fundamental research and applications. The microstrip antenna works in the frequency of 1.27 GHz (L-Band). The microstrip antenna utilized the proximity-coupled method of feeding. Initially, the optimization process of the single patch antenna design involving modifying the microstrip line feed to yield a high gain (above 5 dBi) and low return loss (below -10 dB). A minimum of 10 MHz bandwidth is targeted at below 3 dB of Axial Ratio for the circularly polarized antenna. A planar array from the single patch is formed next. Consideration for the array design is the beam radiation pattern in the azimuth and elevation plane which is specified based on the electrical and mechanical constraints of the UAV CP-SAR system. This research will contribute in the field of radar for remote sensing technology. The potential application is for landcover, disaster monitoring, snow cover, and oceanography mapping.

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KITSAT-3 Image Product Generation System

  • Shin, Dong-Seok;Choi, Wook-Hyun;Kwak, Sung-Hee;Kim, Tag-Gon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.43-47
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    • 1999
  • In this paper, we describe the configuration of the KITSAT-3 image data receiving, archiving, processing and distribution system in operation. Following the low-cost and software-based design concept, the whole system is composed of three PCs : two for data receiving, archiving and processing which provide a full dual-redundant configuration and one for image catalog browsing which can be accessed by public users. Except that receiving and archiving PCs have serial data ingest boards plugged in, they are configured by general peripherals. This basic and simple hardware configuration made it possible to show that a very low cost system can support a full ground operation for the utilization of high-resolution satellite image data.

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Correction and Positioning of Remote Sensing Image Base on Orbit Parameter

  • Cheng, Chunquan;Zhang, Jixian;Yan, Qin;Wang, Yali
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1212-1214
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    • 2003
  • The usual technique of correction and positioning of film image of RS require enough control points to provide the geographic coordinate. Some distortion and error caused by earth curvature and terrain and photograph tilt can't be eliminated by these ways. In this paper a set of technique of systemic correction and positioning of remote sensing image base on orbit parameter is described, some questions in its realization and their solvent also included.

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Some Further Consideration for the Image Retrieving of Synthetic Aperture Radiometer

  • Liu, Hao;Wu, Ji;Wu, Qiong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1349-1351
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    • 2003
  • In this paper, theoretical channels model of Synthetic Aperture Radiometer is presented. Based on this model, how amplitude imbalance, phase imbalance and mutual coupling between the different channels effect brightness temperature image retrieving is analyzed. The computer simulation results are also presented to find out the cause of the along-track streaks usually appeared in the retrieved brightness temperature image. In addition, a new system calibration approach is introduced to solve this problem.

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Road Extraction Based on Watershed Segmentation for High Resolution Satellite Images

  • Chang, Li-Yu;Chen, Chi-Farn
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.525-527
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    • 2003
  • Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

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