• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.645-650
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• 2015

Image restoration is required when the image is blurred due to out of focus or motion during the image acquisition. This type of image restoration is known as ill-posed inverse problem because the estimate of an original image should be derived from only one blurred image. This paper introduces a reference image to facilitate the restoration process. The experimental result shows that computation time is significantly reduced, compared with other methods. The proposed method obtains the estimate of the kernel used in blurring processing. New cost function is defined to update both the image and the kernel alternately. In the last stage, Wiener filter produces the estimate of an original image using the kernel and the reference image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10B
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• pp.1428-1435
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• 2001

본 논문에서는 이미지 데이터의 저작권 보호를 위해 영상변형, JPEG 손실 압축 및 임펄스 잡음에 효과적인 새로운 DM/SS (Direct Matrix/Spread Spectrum) 이미지 워터마킹 기법을 제안한다. 제안하는 기법은 워터마크 영상을 저작권자의 개인 ID (IDentification)로 확산시킨 다음, 원 영상에 삽입하고 역확산시켜 복원하는 방법이다. 원터마크 영상은 2진 영상을 사용하고, 워터마크 시스템에서 요구되는 비가시성과 외부 공격에 대한 워터마크의 강인성을 확인하기 위하여 PSNR (Peak Signal to Noise Ratio)과 워터마크 영상의 복원율 (reconstructive rate)을 구한다. 실험 결과, 워터마크가 삽입된 영상의 PSNR은 93.75 dB로 화질저하가 거의 없었고, 확산 이득으로 인하여 32$\times$32 워터마크 영상이 삽입된 영상에서 우수한 워터마크 영상의 복원율을 얻는다는 것을 보인다. 영상변형 및 JPEG 손실 압축 하에서도 우수한 워터마크 복원 결과를 보였고, 임펄스 잡음이 첨가된 영상의 PSNR이 5.54 dB인 경우에도 효과적으로 워터마크 영상을 복원할 수 있다는 것을 알 수 있었다.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.173-180
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• 2004

In this paper we provide a new image restoration method based on the multiscale regularization in the redundant wavelet transform domain. The proposed method uses the redundant wavelet transform to decompose the single-scale image restoration problem to multiscale ones and applies scale dependent regularization to the decomposed restoration problems. The proposed method recovers sharp edges by applying rather less regularization to wavelet related restorations, while suppressing the resulting noise magnification by the wavelet shrinkage algorithm. The improved performance of the proposed method over more traditional Wiener filtering is shown through numerical experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.232-238
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• 2003

In this paper, we propose a spatially adaptive image restoration algorithm using local statistics. The local mean, variance, and maximum values are utilized to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. A parameter defined by the user determines the degree of local smoothness imposed on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained. Experimental results demonstrate the capability of the proposed algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.66-68
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• 2018

본 논문에서는 비디오로부터 추출된 프레임에서 3D 인체 모델의 복원하고 이를 부드럽게 재생될 수 있도록 보정하는 기법을 제안한다. 매개변수 기반의 모델을 사용하여 자세 및 체형을 복원하도록 접근하고 있다. 매개변수 기반의 인체 모델은 다양한 인체 데이터의 학습을 통해 만들어지며 입력 영상으로부터 최적의 자세와 체형 매개변수 값을 찾아 복원하게 된다. 자세 복원은 CNN 을 사용하여 영상으로부터 인체의 관절 위치를 추정하고 3D 모델로부터 2D 로 투영을 통해 관절 간의 거리가 최소화되는 매개변수 값을 찾아 복원한다. 형상 복원은 2D 영상으로부터 취득된 사람의 윤곽 데이터와 3D 모델의 윤곽 데이터 간의 매칭을 통해 복원된다. 이러한 단일 입력 영상에서 비디오와 같은 다중 입력 영상으로 확장하여 칼만 필터를 적용하여 오류 프레임을 검출하고 이전, 이후 프레임의 매개변수와의 보간을 통해 보다 자연스럽고 정확한 모델을 생성한다.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.18-23
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• 2008

In this paper, we propose the input image selection-method to improve the reconstructed high-resolution (HR) image quality. To obtain ideal super-resolution (SR) reconstruction image, all input images are well-registered. However, the registration is not ideal in practice. Due to this reason, the selection of input images with low registration error (RE) is more important than the number of input images in order to obtain good quality of a HR image. The suitability of a candidate input image can be determined by using statistical and restricted registration properties. Therefore, we propose the proper candidate input Low Resolution(LR) image selection-method as a pre-processing for the SR reconstruction in automatic manner. In video sequences, all input images in specified region are allowed to use SR reconstruction as low-resolution input image and/or the reference image. The candidacy of an input LR image is decided by the threshold value and this threshold is calculated by using the maximum motion compensation error (MMCE) of the reference image. If the motion compensation error (MCE) of LR input image is in the range of 0 < MCE < MMCE then this LR input image is selected for SR reconstruction, else then LR input image are neglected. The optimal reference LR (ORLR) image is decided by comparing the number of the selected LR input (SLRI) images with each reference LR input (RLRI) image. Finally, we generate a HR image by using optimal reference LR image and selected LR images and by using the Hardie's interpolation method. This proposed algorithm is expected to improve the quality of SR without any user intervention.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.264-272
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• 2010

Example-based super resolution is a method to restore a high resolution image from low resolution images through training and retrieval of image patches. It is not only good in its performance but also available for a single frame low-resolution image. However, its time complexity is very high because it requires lots of comparisons to retrieve image patches in restoration process. In order to improve the restoration speed, an efficient patch retrieval algorithm is essential. In this paper, we applied various high-dimensional feature retrieval methods, available for the patch retrieval, to a practical example-based super resolution system and compared their speed. As well, we propose to apply the multi-phase candidate reduction approach to the patch retrieval process, which was successfully applied in character recognition fields but not used for the super resolution. In the experiments, LSH was the fastest among conventional methods. The multi-phase candidate reduction method, proposed in this paper, was even faster than LSH: For $1024{\times}1024$ images, it was 3.12 times faster than LSH.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1759-1771
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• 1994

We proposed the iterative image restoration method based on the method of steepest descent with a regularization constraint for restoring the noisy motion-blurred images. The conventional method proposed by Jan Biemond et al, had drawback to amplify the additive noise and make ringing effects in the restored images by determining the value of regularization parameter experimentally from the degraded image to be restored without considering local information of the restored one. The method we proposed had a merit to suppress the noise amplification and restoration error by using the regularization parameter which estimate the value of it adaptively from each pixels of the image being restored in order to reduce the noise amplification and ringing effects efficiently. Also we proposed the termination rule to stop the iteration automatically when restored results approach into or diverse from the original solution in satisfaction. Through the experiments, proposed method showed better result not only in a MSE of 196 and 453 but also in the suppression of the noise amplification in the flat region compared with those proposed by Jan Biemond et al. of which MSE of 216 and 467 respectively when we used 'Lean' and 'Jaguar' images as original images.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.345-348
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• 2000

본 논문에서는 웨이브릿 변환과 유전자 알고리즘을 이용한 하이브리드 영상복원 방법을 제안한다. 제안한 방법은 영상복원을 위한 전처리로써 분해 및 합성 필터의 이상적인 직교 특성을 가지는 웨이브릿 변환을 이용하여 잡음훼손영상으로부터 고주파성 잡음의 일부를 우선 제거하고 나머지 영상에 대해서는 국부적 최적해로의 고립을 벗어나 전역해 탐색이 가능한 유전자 알고리즘을 적용한다 제안한 하이브리드 방법의 성능평가를 위하여 이진 문자영상과 Lenna 영상을 입력영상으로 인가하여 기존의 단일 유전자 알고리듬을 이용한 방법과 비교실험을 수행하였다. 실험결과 제안한 하이브리드 영상 복원방법이 기존의 방법에 비하여 약 2dB 향상됨으로써 잡음훼손영상의 복원성능이 우수함을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.217-220
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• 2010

본 논문에서는 단점과 분기점을 이용한 세선화 영상 복원에 관하여 연구하였다. 이진 지문영상으로부터 평활화, 이진화, 세선화 과정을 거쳐서 세선화 영상을 얻는다. 세선화 영상으로부터 특징점을 추출하는 방법에는 교차수를 이용한 방법이 있다. 그러나 교차수를 이용한 방법에서는 많은 의사 특징점들이 추출된다. 의사특징점으로는 단선, 절선, 잔가지, 원형 등이 있으며, 단점과 분기점을 이용하여 의사특징점을 제거함으로써 세선화 영상을 복원하였다.