• Title/Summary/Keyword: ocean image

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A Modulation Transfer Function Compensation for the Geostationary Ocean Color Imager (GOCI) Based on the Wiener Filter

  • Oh, Eunsong;Ahn, Ki-Beom;Cho, Seongick;Ryu, Joo-Hyung
    • Journal of Astronomy and Space Sciences
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    • v.30 no.4
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    • pp.321-326
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    • 2013
  • The modulation transfer function (MTF) is a widely used indicator in assessments of remote-sensing image quality. This MTF method is also used to restore information to a standard value to compensate for image degradation caused by atmospheric or satellite jitter effects. In this study, we evaluated MTF values as an image quality indicator for the Geostationary Ocean Color Imager (GOCI). GOCI was launched in 2010 to monitor the ocean and coastal areas of the Korean peninsula. We evaluated in-orbit MTF value based on the GOCI image having a 500-m spatial resolution in the first time. The pulse method was selected to estimate a point spread function (PSF) with an optimal natural target such as a Seamangeum Seawall. Finally, image restoration was performed with a Wiener filter (WF) to calculate the PSF value required for the optimal regularization parameter. After application of the WF to the target image, MTF value is improved 35.06%, and the compensated image shows more sharpness comparing with the original image.

Algorithm to Estimate Oil Spill Area Using Digital Properties of Image

  • Jang, Hye-Jin;Nam, Jong-Ho
    • Journal of Ocean Engineering and Technology
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    • v.34 no.1
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    • pp.46-54
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    • 2020
  • Oil spill accidents at sea result in a wide range of damages, including the destruction of ocean environments and ecosystems, as well as human illnesses by the generation of harmful gases caused by phase changes in crude oil. When an oil spill occurs, an immediate initial action should be performed to minimize the potential damage. Existing studies have attempted to identify crude oil spillage by calculating the crude oil spill range using synthetic aperture radar (SAR) satellite images. However, SAR cannot capture rapidly evolving events because of its low acquisition frequency. Herein, an algorithm for estimating an oil spill area from an image obtained using a digital camera is proposed. Noise that may occur in the image when it is captured is first eliminated by preprocessing, and then the image is analyzed. After analyzing the characteristics of the digital image, a strategy to binarize an image using the color, saturation, or lightness contained in it is adopted. It is found that the oil spill area can be readily estimated from a digital image, allowing for a faster analysis than any conventional method. The usefulness of the oil spill area measurement was confirmed by applying the developed algorithm to various oil spill images.

ANALYSIS OF OCEAN WAVE BY AIRBORNE PI-SAR X-BAND IMAGES

  • Yang, Chan-Su;Ouchi, Kazuo
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.240-242
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    • 2008
  • In the present article, we analyze airborne Pi-SAR (Polarimetric-Interferometric SAR) X-band images of ocean waves around the Miyake Island at approximately 180 km south from Tokyo, Japan. Two images of a same scene were produced at approximately 40 min. interval from two directions at right angles. One image shows dominant range travelling waves, but the other image shows a different wave pattern. This difference can be caused by the different image modulations of RCS and velocity bunching. We have estimated the dominant wavelength from the image of range waves, and from the wave phase velocity computed from the dispersion relation (though no wave height data were available), the image intensity is computed by using the velocity bunching model. The comparison of the result with the second image at right angle strongly suggests the evidence of velocity bunching.

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Comparison of GAN Deep Learning Methods for Underwater Optical Image Enhancement

  • Kim, Hong-Gi;Seo, Jung-Min;Kim, Soo Mee
    • Journal of Ocean Engineering and Technology
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    • v.36 no.1
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    • pp.32-40
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    • 2022
  • Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

Backup Site Operation Of COMS Image Data Acquisition And Control System (천리안위성 영상 수신 및 처리에 대한 백업 지상국 운영)

  • Cho, Young-Min;Kwon, Eun Joo
    • Journal of Satellite, Information and Communications
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    • v.10 no.2
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    • pp.95-101
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    • 2015
  • The backup site operation of the Image Data Acquisition and Control System (IDACS) for Communication Ocean Meteorological Satellite (COMS) is discussed in terms of the ground station configuration, image data processing, and the characteristics of backup activities for both the meteorological image data and the ocean image data. The well-performed backup operation of the COMS IDACS is also confirmed with the first three years normal operation results from April, 2011 to March, 2014. The operation results are analyzed through statistical approach to provide the achieved operational performance of the image data reception, preprocessing, and broadcast.

Ocean Scanning Multi-spectral Imager (OSMI) Pre-Launch Radiometric Performance Analysis

  • Cho, Young-Min
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.390-395
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    • 1999
  • Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

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Single Image-based Enhancement Techniques for Underwater Optical Imaging

  • Kim, Do Gyun;Kim, Soo Mee
    • Journal of Ocean Engineering and Technology
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    • v.34 no.6
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    • pp.442-453
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    • 2020
  • Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

Study of an AI Model for Airfoil Parameterization and Aerodynamic Coefficient Prediction from Image Data (이미지 데이터를 이용한 익형 매개변수화 및 공력계수 예측을 위한 인공지능 모델 연구)

  • Seung Hun Lee;Bo Ra Kim;Jeong Hun Lee;Joon Young Kim;Min Yoon
    • Journal of the Korean Society of Visualization
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    • v.21 no.2
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    • pp.83-90
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    • 2023
  • The shape of an airfoil is a critical factor in determining aerodynamic characteristics such as lift and drag. Aerodynamic properties of an airfoil have a decisive impact on the performance of various engineering applications, including airplane wings and wind turbine blades. Therefore, it is essential to analyze the aerodynamic characteristics of airfoils. Various analytical tools such as experiments, computational fluid dynamics, and Xfoil are used to perform these analyses, but each tool has its limitation. In this study, airfoil parameterization, image recognition, and artificial intelligence are combined to overcome these limitations. Image and coordinate data are collected from the UIUC airfoil database. Airfoil parameterization is performed by recognizing images from image data to build a database for deep learning. Trained model can predict the aerodynamic characteristics not only of airfoil images but also of sketches. The mean absolute error of untrained data is 0.0091.

Concealment of iris features based on artificial noises

  • Jiao, Wenming;Zhang, Heng;Zang, Qiyan;Xu, Weiwei;Zhang, Shuaiwei;Zhang, Jian;Li, Hongran
    • ETRI Journal
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    • v.41 no.5
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    • pp.599-607
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    • 2019
  • Although iris recognition verification is considered to be the safest method of biometric verification, studies have shown that iris features may be illegally used. To protect iris features and further improve the security of iris recognition and verification, this study applies the Gaussian and Laplacian mechanisms and to hide iris features by differentiating privacy. The efficiency of the algorithm and evaluation of the image quality by the image hashing algorithm are selected as indicators to evaluate these mechanisms. The experimental results indicate that the security of an iris image can be significantly improved using differential privacy protection.

A Study on Radar Image Simulation for Ocean Waves Using Radar Received Power (파랑에 관한 레이더 이미지 시뮬레이션을 위한 레이더 수신 출력 도입 기법 연구)

  • Park, Jun-Soo;Yang, Young-Jun;Park, Seung-Gun;Kwon, Sun-Hong
    • Journal of Ocean Engineering and Technology
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    • v.24 no.1
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    • pp.47-52
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    • 2010
  • This study presents a modified scheme for the radar image simulation of sea waves. A simulated radar image was obtained by taking into account the dot product of the directed vector from the radar and the normal vector of the sea surface. Moreover, to calculate the radar image, we used the radar received power and radar cross section. To demonstrate the effectiveness of the proposed scheme, the wave spectrum from field data was utilized to obtain the simulated sea waves. The radar image was simulated using numerically generated sea waves. The wave statistics from the simulation agrees comparatively with those of the original field data acquired by real radar measurements.