• 제목/요약/키워드: Restoration Image

검색결과 732건 처리시간 0.026초

경계왜곡 제거방법을 이용한 고속 영상복원 (Fast Image Restoration Using Boundary Artifacts Reduction method)

  • 임성준;김동균;신정호;백준기
    • 대한전자공학회논문지SP
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    • 제44권6호
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    • pp.63-74
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    • 2007
  • 고속 퓨리에 변환(Fast Fourier Transform: FFT)은 입력신호가 주기적이라는 가정하에 빠른 계산량과 좋은 성능으로 영상복원에 다방면으로 적용되고 있다. 하지만 실제취득영상은 주기가 무한한 영역의 일부분을 한 주기로 가정하고, 또한 외부영역에 대한 정보손실로 인하여 경계왜곡이 발생한다. 본 논문은 현재까지 진행되어온 경계왜곡을 줄이기 위한 기술들에 대해 고찰정리 하였다. 뿐만 아니라 FFT의 계산량 감소를 위해 블록기반의 영상처리와 이때 발생하는 경계왜곡 감소를 위한 알고리듬을 제안한다. 외부영역의 정보를 알고 있는 경우의 보다 좋은 결과를 위하여 안쪽 블록과 바깥블록의 처리를 달리 적용하였다. 이러한 과정을 통해 경계왜곡을 줄이면서 고속으로 영상복원을 가능하게 한다.

다중척도 정칙화 방법을 이용한 영상복원 (Multiscale Regularization Method for Image Restoration)

  • 이남용
    • 융합신호처리학회논문지
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    • 제5권3호
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    • pp.173-180
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    • 2004
  • 이 논문에서는 중복된 웨이블렛 변환영역에서 다중척도 정칙화를 이용한 새로운 영상복원방법을 제시하였다. 제안된 방법은 중복된 웨이블렛 변환을 이용하여 단일척도 영상복원문제를 다중척도의 영상복원문제로 변환한 후에, 각 척도에 의존하는 정칙화 방법을 이용하여 각 척도별로 영상복원을 하고 그 결과를 중복 웨이블렛 역변환을 통해 최종적인 영상복원을 얻는 방법이다. 제안된 방법은 웨이블렛 관련 복원부분에서는 다소 적은 정칙화 계수를 적용하여 뚜렷한 경계를 복원하는 반면, 적은 정칙화 계수에 적용한 것에 의해 발생하는 잡음은 웨이블렛 축소법을 이용하여 제거하였다. 제안된 방법의 향상된 영상복원 성능은 전통적인 Wiener 필터링과의 비교실험을 통해 검증하였다.

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Restoration of underwater images using depth and transmission map estimation, with attenuation priors

  • Jarina, Raihan A.;Abas, P.G. Emeroylariffion;De Silva, Liyanage C.
    • 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.

THE CONSTRAINED ITERATIVE IMAGE RESTORATION ALGORITHM USING NEW REGULARIZATION OPERATORS

  • Lee, Sang-Hwa;Lee, Choong-Woong
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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    • pp.107-112
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    • 1997
  • This paper proposes the regularized constrained iterative image restoration algorithms which apply new space-adaptive methods to degraded image signals, and analyzes the convergence condition of the proposed algorithm. First, we introduce space-adaptive regularization operators which change according to edge characteristics of local images in order to effectively prevent the restored edges and boundaries from reblurring. And, pseudo projection operator is used to reduce the ringing artifact which results from extensive amplification of noise components in the restoration process. The analysed algorithm is stable convergent to the fixed point. According to the experimental results for various signal-to-noise ratios(SNR) and blur models, the proposed algorithms other methods and is robust to noise effects and edge reblurring by regularization especially.

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Exploring Image Processing and Image Restoration Techniques

  • Omarov, Batyrkhan Sultanovich;Altayeva, Aigerim Bakatkaliyevna;Cho, Young Im
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제15권3호
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    • pp.172-179
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    • 2015
  • Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.

복구패턴 정합을 통한 기하학적 왜곡에 적응적인 워터마킹 (Watermarking Algorithm that is Adaptive on Geometric Distortion in consequence of Restoration Pattern Matching)

  • 전영민;고일주;김동호
    • 정보처리학회논문지B
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    • 제12B권3호
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    • pp.283-290
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    • 2005
  • 워터마킹에서 영상의 평행이동, 회전, 크기변환 왜곡에 기인한 워터마크 삽입 위치와 추출 위치의 불일치는 해결해야 하는 문제이다. 본 논문에서는 복구패턴 정합을 통한 영상동기화를 이용함으로써 기하학적 왜곡에 강인한 워터마킹 방법을 제안한다. 제안하는 방법은 복구패턴을 정의하여 워터마크가 삽입된 영상에 복구패턴을 삽입 배포한다. 그리고 배포된 영상으로부터 복구패턴을 추출하여 삽입한 복구패턴과 비교함으로써 기하학적 왜곡 여부를 확인한다 기하학적 왜곡이 발생하였다면 왜곡된 만큼 역변환을 함으로써 워터마크 삽입 위치와 추출 위치를 동기화 한다. 제안한 방법의 성능을 평가하기 위하여 이동, 회전, 스케일링 공격에 대한 실험결과를 보인다.

Fast Iterative Image Restoration Algorithm

  • Moon, J.I.;Paik, J.K.
    • Journal of Electrical Engineering and information Science
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    • 제1권2호
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    • pp.67-76
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    • 1996
  • In the present paper we propose two new improved iterative restoration algorithms. One is to accelerate convergence of the steepest descent method using the improved search directions, while the other accelerates convergence by using preconditioners. It is also shown that the proposed preconditioned algorithm can accelerate iteration-adaptive iterative image restoration algorithm. The preconditioner in the proposed algorithm can be implemented by using the FIR filter structure, so it can be applied to practical application with manageable amount of computation. Experimental results of the proposed methods show good perfomance improvement in the sense of both convergence speed and quality of the restored image. Although the proposed methods cannot be directly included in spatially-adaptive restoration, they can be used as pre-processing for iteration-adaptive algorithms.

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Restoring Turbulent Images Based on an Adaptive Feature-fusion Multi-input-Multi-output Dense U-shaped Network

  • Haiqiang Qian;Leihong Zhang;Dawei Zhang;Kaimin Wang
    • Current Optics and Photonics
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    • 제8권3호
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    • pp.215-224
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    • 2024
  • In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

RESTORATION OF BLURRED IMAGES BY GLOBAL LEAST SQUARES METHOD

  • Chung, Sei-young;Oh, SeYoung;Kwon, SunJoo
    • 충청수학회지
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    • 제22권2호
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    • pp.177-186
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    • 2009
  • The global least squares method (Gl-LSQR) is a generalization of LSQR method for solving linear system with multiple right hand sides. In this paper, we present how to apply this algorithm for solving the image restoration problem and illustrate the usefulness and effectiveness of this method from numerical experiments.

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무선 멀티미디어 통신 환경에서 정지영상 전송에 삽입되는 디지털 워터마킹에 관한 연구 (A Study on the Digital Watermarking Embedded Transmission of Still Image in Wireless Multimedia Communication Environment)

  • 조송백;이양선;강희조
    • 한국항행학회논문지
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    • 제8권2호
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    • pp.169-175
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    • 2004
  • 본 논문에서는 무선 멀티미디어 통신 환경에서 정지영상 전송에 삽입되는 디지털 워터마킹에 관하여 분석하였다. 또한, 기존의 이미지를 사용한 방법보다 원 영상에 미치는 영향이 적고 외부공격으로부터 강인한 워터마크 복원 능력을 보이는 개선된 워터마크 기법을 제안 하였다. 성능분석으로써 무선 멀티미디어 서비스를 위해 OFDM/QPSK 영상전송 시스템을 이용하여 무선채널 환경에서의 정지영상 이미지와 워터마크로 사용된 정보에 미치는 영향을 분석하였다. 분석 결과, 본 논문에서 제안한 VI 워터마크를 삽입함으로써 원영상에 미치는 영향이 매우작고, 높은 복원 성능을 보여줌을 알 수 있었다. 또한, 동일한 전송에러 조건의 무선 채널환경에서 이미지 워터마크에 비해 우수한 저작권 정보 추출 성능을 보였다.

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