• 보존과학회지
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• 제38권1호
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• pp.14-32
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• 2022

Underwater photographing and image recording are essential for pre-excavation survey and during excavation in underwater archaeology. Unlike photographing on land, all underwater images suffer various quality degradations such as shape distortions, color shift, blur, low contrast, high noise levels and so on. Outcome is very often heavily photographing equipment and photographer dependent. Excavation schedule, weather conditions, and water conditions can put burdens on divers. Usable images are very limited compared to the efforts. In underwater archaeological study in very turbid water such as in the Yellow Sea (between mainland China and the Korean peninsula), underwater photographing is very challenging. In this study, off-site image distortion and color compensation techniques using an image processing/analysis software is investigated as an alternative image quality enhancement method. As sample images, photographs taken during the excavation of 800-year-old Taean Mado Shipwrecks in the Yellow Sea in 2008-2010 were mainly used. Significant enhancement in distortion and color compensation of archived images were obtained by simple post image processing using image processing/analysis software (PicMan) customized for given view ports, lenses and cameras with and without optical axis offsets. Post image processing is found to be very effective in distortion and color compensation of both recent and archived images from various photographing equipment models and configurations. Merits and demerit of in-situ, distortion and color compensated photographing with sophisticated equipment and conventional photographing equipment, which requires post image processing, are compared.

• Journal of Advanced Marine Engineering and Technology
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• 제33권2호
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• pp.344-354
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• 2009

Side scan sonar using acoustic wave plays a very important role in the underwater, sea floor, and shallow marine geologic survey. In this study, we have acquired side scan sonar data for the underwater man-made structures, artificial reefs and fishing grounds, installed and distributed in the survey area. We applied digital image processing techniques to side scan sonar data in order to improve and enhance an image quality. We carried out digital image processing with various kinds of filtering in spatial domain and frequency domain. We tested filtering parameters such as kernel size, differential operator, and statistical value. We could easily estimate the conditions, distribution and environment of artificial structures through the interpretation of side scan sonar.

• 한국음향학회지
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• 제42권4호
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• pp.370-376
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• 2023

수중영상은 수중 잡음과 낮은 해상도로 표적의 형상과 구분이 명확하지 않다. 그리고 딥러닝의 입력으로 수중영상은 전처리가 필요하며 Segmentation이 선행되어야 한다. 전처리를 하여도 표적은 명확하지 않으며 딥러닝에 의한 탐지, 식별의 성능도 높지 않을 수 있다. 따라서 표적을 구분하며 명확하게 하는 작업이 필요하다. 본 연구에서는 수중영상에서 표적 그림자의 중요성을 확인하고 그림자에 의한 물체 탐지 및 표적 영역 획득, 그리고 수중배경이 없는 표적과 그림자만의 형상이 담긴 데이터를 생성하며 더 나아가 픽셀값이 일정하지 않은 표적과 그림자 영상을 표적은 흰색, 그림자는 흑색, 그리고 배경은 회색의 3-모드의 영상으로 변환하는 과정을 제시한다. 이를 통해 딥러닝의 입력으로 명확히 전처리된 판별이 용이한 영상을 제공할 수 있다. 또한 처리는 Open Source Computer Vision(OpenCV)라이브러리의 영상처리 코드를 사용했으면 처리 속도도 역시 실시간 처리에 적합한 결과를 얻었다.

• Ocean Systems Engineering
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• 제6권3호
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• 한국해양공학회지
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• 제36권1호
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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.

• 융합신호처리학회논문지
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• 제11권3호
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• pp.203-208
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• 2010

본 논문에서는 소나 시스템을 통해 획득된 수중 음향 신호를 디지털 영상의 형태로 변환한다. 그리고 이러한 형태의 영상에 대해 영상 처리 기법을 도입하여 표적 후보를 탐지하고, 이들 영역에 대해 정보를 강화하는 알고리즘을 제안한다. 수중 표적의 탐지 과정은 우선 수중음향신호 영상에서 불규칙한 형태로 분포하고 있는 배경 잡음을 추정하여 재구성한 뒤, 원 영상에서 배경 영상을 제거하여 초기 표적 후보군을 획득한다. 또한 도플러 신호 정보를 가공하여 가중치 맵을 생성하고, 배경잡음이 제거된 영상에 대해 가중치 맵을 이용한 필터링 과정을 수행함으로써 표적 후보에 대한 정보를 보다 정확히 확보하고, 단일프레임에서의 표적 후보 정보를 강화한다. 본 논문에서는 시뮬레이션으로 획득된 수중음향신호에 대해 제안된 알고리즘을 적용하여, 불규칙적으로 발생하게 되는 잡음이 대부분 제거됨을 확인하였고, 필터링 및 표적 탐지 과정을 통해 수중음향신호 영상에서 표적이 더욱 명확히 표시됨을 확인하였다.

• 전자공학회논문지
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• 제53권3호
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• pp.91-98
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• 2016

소나 영상에서 수중 물체의 검출과 분류는 도전적인 과제이다. 본 논문에서는 소나 영상과 영상처리기법을 이용하여 해저의 물체를 식별하는 시스템을 제안한다. 수중 물체의 식별 과정은 수중 물체 후보 영역 검출과 물체 식별의 두 단계로 구성된다. 영상 정합(image registration) 기법을 이용하여 수중 물체 후보 영역을 검출하고, 기존에 획득된 기준 배경 영상과 현재 스캔된 영상 사이의 공통된 특징점을 검출하여 정합한 후, 두 영상의 차 영상(difference image)을 구하여 검출한다. 검출된 물체는 고유벡터와 고유값을 특징으로 사용하여 데이터베이스내의 패턴과 가장 유사한 패턴으로 분류한다. 제안하는 수중 물체 식별 시스템은 최단 소행 항로(Q route) 확보와 같은 응용에 효율적으로 사용될 수 있을 것으로 기대된다.

• 융합신호처리학회논문지
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• 제24권1호
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• pp.1-14
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• 2023

Underwater images carry information that is useful in the fields of aquaculture, underwater military security, navigation, transportation, and so on. In this research, we transmitted an underwater image through various underwater mediums in the presence of underwater turbulence and beam attenuation effects using a high-speed visible optical carrier signal. The optical beam undergoes scintillation because of the turbulence and attenuation effects; therefore, distorted images were observed at the receiver end. To understand the behavior of the communication media, we obtained the bit error rate (BER) performance of the system with respect to the average signal-to-noise ratio (SNR). Also, the structural similarity index (SSI) and peak SNR (PSNR) metrics of the received image were evaluated. Based on the received images, we employed suitable nonlinear filters to recover the distorted images and enhance them further. The BER, SSI, and PSNR metrics of the specific nonlinear filters were also evaluated and compared with the unfiltered metrics. These metrics were evaluated using the on-off keying and binary phase-shift keying modulation techniques for the 50-m and 100-m links for beam attenuation resulting from pure seawater, clear ocean water, and coastal ocean water mediums.

• 보존과학회지
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• 제37권4호
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• pp.312-321
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• 2021

Underwater archaeology relies heavily on photography and video image recording during surveillances and excavations like ordinary archaeological studies on land. All underwater images suffer poor image quality and distortions due to poor visibility, low contrast and blur, caused by differences in refractive indices of water and air, properties of selected lenses and shapes of viewports. In the Yellow Sea (between mainland China and the Korean peninsula), the visibility underwater is far less than 1 m, typically in the range of 30 cm to 50 cm, on even a clear day, due to very high turbidity. For photographing 1 m x 1 m grids underwater, a very wide view angle (180°) fisheye lens with an 8 mm focal length is intentionally used despite unwanted severe barrel-shaped image distortion, even with a dome port camera housing. It is very difficult to map wide underwater archaeological excavation sites by combining severely distorted images. Development of practical compensation methods for distorted underwater images acquired through the fisheye lens is strongly desired. In this study, the source of image distortion in underwater photography is investigated. We have identified the source of image distortion as the mismatching, in optical axis and focal points, between dome port housing and fisheye lens. A practical image distortion compensation method, using customized image processing software, was explored and verified using archived underwater excavation images for effectiveness in underwater archaeological applications. To minimize unusable area due to severe distortion after distortion compensation, practical underwater photography guidelines are suggested.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.316-320
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• 2003

This paper introduces an autonomous underwater vehicle (AUV) model, ASUM, equipped with a visual servo control system to dock into an underwater station with a camera and motion sensors. To make a visual servoing AUV, this paper implemented the visual servo control system designed with an augmented state equation, which was composed of the optical flow model of a camera and the equation of the AUV's motion. The system design and the hardware configuration of ASUM are presented in this paper. ASUM recognizes the target position by processing the captured image for the lights, which are installed around the end of the cone-type entrance of the duct. Unfortunately, experiments are not yet conducted when we write this article. The authors will present the results for the AUV docking test.