• Ocean Systems Engineering
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• 제11권4호
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• pp.331-351
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• 2021

Underwater images are very much different from images taken on land, due to the presence of a higher disturbance ratio caused by the presence of water medium between the camera and the target object. These distortions and noises result in unclear details and reduced quality of the output image. An underwater image restoration method is proposed in this paper, which uses blurriness information, background light neutralization information, and red-light intensity to estimate depth. The transmission map is then estimated using the derived depth map, by considering separate attenuation coefficients for direct and backscattered signals. The estimated transmission map and estimated background light are then used to recover the scene radiance. Qualitative and quantitative analysis have been used to compare the performance of the proposed method against other state-of-the-art restoration methods. It has been shown that the proposed method can yield good quality restored underwater images. The proposed method has also been evaluated using different qualitative metrics, and results have shown that method is highly capable of restoring underwater images with different conditions. The results are significant and show the applicability of the proposed method for underwater image restoration work.

• 반도체디스플레이기술학회지
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• 제23권2호
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• pp.23-27
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• 2024

Underwater images are typically degraded due to color distortion, light absorption, scattering, and noise from artificial light sources. Restoration of these images is an essential task in many underwater applications. In this paper, we propose a two-phase deep learning-based method, Underwater Deep Curve Estimation (UWDCE), designed to effectively enhance the quality of underwater images. The first phase involves a white balancing and color correction technique to compensate for color imbalances. The second phase introduces a novel deep learning model, UWDCE, to learn the mapping between the color-corrected image and its best-fitting curve parameter maps. The model operates iteratively, applying light-enhancement curves to achieve better contrast and maintain pixel values within a normalized range. The results demonstrate the effectiveness of our method, producing higher-quality images compared to state-of-the-art methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 D
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• pp.1537-1539
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• 1998

In this study, 3-D underwater object restoration using ultrasonic transducer fabricated with PZT-Polymer 1-3 type composite are presented. Using the acquired underwater object data 16${\times}$16 pixels. Modified SCL neural networks using the 16${\times}$16 low resolution image was used for underwater object restoration of 32${\times}$32 high resolution Image.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 C
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• pp.1373-1375
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• 1997

In this study, 3-D underwater object restoration using ultrasonic sensor fabricated with porous PZT-Polymer 3-3 type composite are presented Using the acquired underwater object data $16{\times}16$ pixels, Modified SCL neural networks using the $16{\times}16$ low resolution image was used for underwater object restoration of $32{\times}32$ high resolution image.

• E2M - 전기 전자와 첨단 소재
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• 제9권8호
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• pp.825-830
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• 1996

In this study, Characteristics of Ultrasonic Transducer fabricated with porous piezoelectric resonator, 3-D underwater object restoration using the self made ultrasonic transducer and modified SCL(Simple Competitive Learning) neural network are investigated. The self-made transducer was satisfied the required condition of ultrasonic transducer in water, and the modified SCL neural network using the acquired object data 16*16 low resolution image was used for object restoration of $32{\times}32$ high resolution image. The experimental results have shown that the ultrasonic transducer fabricated with porous piezoelectric resonator could be applied for SONAR system.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제48권6호
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• pp.456-461
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• 1999

In this study, the characteristics of Ultrasonic Transducer fabricated with PZT-Polymer 1-3 type piezoelectric ceramic/polymer composite are investigated. 3-D underwater object restoration using the self-made ultrasonic transducer and modified SCL(Simple Competitive Learning) neural network was presented. The ultrasonic transducer was satisfied with the required condition of commerical ultrasonic transducer in underwater. The modified SCL neural network using the acquired object data $16\times16$ low resolution image was used for object restoration of $32\times32$ high resolution image. The experimental results have shown that the ultrasonic transducer fabricated with PZT-Polymer 1-3 type piezoelectric ceramic/polymer composite could be applied for SONAR system.

• 한국음향학회지
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• 제37권1호
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• pp.12-20
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• 2018

측면주사 소나 영상 획득의 효율성을 향상시키고자 저해상도의 수중 영상을 복원 기법을 이용하여 고화질 영상으로 개선시키는 연구가 시도되고 있다. 측면주사 소나 영상은 광학 영상과 같은 2차원 신호를 사용한다는 측면에서 기존 광학 영상 복원에 적용된 기법의 응용을 고려할 수 있다. 광학 영상에 대한 가장 대표적인 복원 방법 중 하나는 스파스 코딩이며, 수중 영상의 희소성을 분석하여 스파스 코딩 기법을 수중 영상에 적용할 수 있음을 증명하는 연구가 진행되었다. 스파스 코딩은 입력 신호에 대하여 사전과 스파스 계수의 선형 결합으로 복원 신호를 얻는 방식이다. 하지만 스파스 계수의 값을 정확히 추정하기 위해서는 많은 연산량을 필요로 한다. 본 연구에서는 스파스 코딩 기반의 수중 영상 초해상도 복원을 수행하되, 수중 영상 내 객체 영역에 한해서 선택적으로 복원 기법을 적용하는 방법을 제안함으로써 전체 연산 시간을 단축시킨다. 이를 위하여 수중 영상에서 경계를 검출하고 그 분포에 따라 객체 영역과 비객체 영역을 구분하는 방법을 제안하고, 이를 스파스 코딩 기반의 초해상도 복원 기법과 접목시킨다. 실험을 통해 제안하는 방법이 기존 방식과 동일 수준의 PSNR(Peak Signal-to-Noise Ratio) 수치를 유지하며, 영상 복원에 필요한 시간은 32 % 만큼 단축시킴을 확인함으로써 제안 방법의 유효성을 증명하였다.