• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.767-774
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• 2002

Conventional research on image restoration has focused on restoring degraded images resulting from image formation, storage and communication, mainly in the signal processing field. Related research on recovering original image information of caption regions includes a method using BMA(block matching algorithm). The method has problem with frequent incorrect matching and propagating the errors by incorrect matching. Moreover, it is impossible to recover the frames between two scene changes when scene changes occur more than twice. In this paper, we propose a method for recovering original images using EBMA(Extended Block Matching Algorithm) and a region compensation method. To use it in original image recovery, the method extracts a priori knowledge such as information about scene changes, camera motion and caption regions. The method decides the direction of recovery using the extracted caption information(the start and end frames of a caption) and scene change information. According to the direction of recovery, the recovery is performed in units of character components using EBMA and the region compensation method. Experimental results show that EBMA results in good recovery regardless of the speed of moving object and complexity of background in video. The region compensation method recovered original images successfully, when there is no information about the original image to refer to.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1980-1987
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• 1999

Restored image is always lower quality than original one due to distortion and noise. The purpose of image restoration is to improve the image quality by fixing the noise or distortion information. One category of spatial filters for image restoration is linear filter. This filter algorithm is easily implemented and can be suppressed the Gaussian noise effectively, but not so good performance for spot or impulse noise. In this paper, we propose the nonlinear spatial filter algorithm for image restoration called the optimal adaptive multistage filter(OAMF). The OAMF is used to reduce the filtering time, increases the noise suppression ratio and preserves the edge information. The OAMF optimizes the adaptive multistage filter(AMF) by using weight learning algorithm of back-propagation learning algorithm. Simulation results of this filter algorithm are presented and discussed.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.1-9
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• 2019

The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.389-393
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• 2008

Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.177-182
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• 2010

Research on recovering original images from captions has been widely done in a reusability point of view. In usual, dynamic images imported from foreign countries often have captions of foreign languages, so it is necessary to translate them into one's language. For the natural exchange of captions without loss of original images, recovering the images corresponding to captions is necessary. However, though recovering original images is very important, systematic analysis on the characteristics of captions has not been done yet. Therefore, in this paper, we first survey the classification methods of TV programs at academic worlds, broadcasting stations, and broadcasting organizations, and then analyses the frequency of captions, importance of caption contents, and necessity of recovering according to their types. Also, we analyze the characteristics of captions which are significantly recognized to be necessary to recover, and use them as recovering information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.1-8
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• 2004

In this paper, we propose a method for restoring trademark and caption areas using an isophote. In our method, the image restoration problem is modeled as an optimization problem, which in our case, is solved by a cost function with isophote constraint that is minimized using a GA The technique creates an optimal connection of all pairs of isophotes disconnected by a caption in the frame. For connecting the disconnected isophotes, we estimate the value of the smoothness, given by the best chromosomes of the GA and project this value in the isophote direction. Experimental results show that the isophote operator worked better than Laplacian operator for image restoration, and the proposed method has a great possibility for automatic restoration of a region in an advertisement scene.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.430-439
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• 2019

The CNN (convolutional neural network) based single degradation restoration method shows outstanding performance yet is tailored on solving a specific degradation type. In this paper, we present an algorithm of multi-degradation classification and restoration. We utilize the CNN based algorithm for solving image degradation classification problem using pre-trained Inception-v3 network. In addition, we use the existing CNN based algorithms for solving particular image degradation problems. We identity the restoration order of multi-degraded images empirically and compare with the non-reference image quality assessment score based on CNN. We use the restoration order to implement the algorithm. The experimental results show that the proposed algorithm can solve multi-degradation problem.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.72-83
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• 2011

In this paper, we propose a method to detect and recover the occluded parts of face images using the correlation between pairs of pixels. In a training stage, correlation coefficients between every pairs of pixels are calculated using the occlusion-free face images. Once a new occluded face image is shown, the occluded area is detected and recovered using the correlation coefficients obtained in the training stage. We compare the performance of the proposed method with the conventional method based on PCA. The results show that the proposed method detects and recovers occluded area with much smaller noises than the conventional PCA based method. Moreover, recovered images by the proposed method were more smooth with reduced blurring effect.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.205-210
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• 2006

본 논문에서는 간섭계와 직렬 위상 카드를 이용한 광 보안 시스템을 제안하였다. 먼저 원영상을 암호화하기 위해 원영상을 암호화하는 것이 아니라 원영상에 대한 이진 위상 컴퓨터형성홀로그램을 반복 알고리즘을 이용하여 구하고, 이진 위상 컴퓨터형성홀로그램과 무작위 생성된 위상 키 영상과의 XOR 연산을 통해 암호화된 영상을 구한다. 홀로그램의 복호화 과정은 암호화된 영상과 암호화시에 사용된 무작위 위상 영상 키를 직렬 정합시킨 후, 기준파와의 간섭에 의해 수행된다. 이때, 간섭패턴은 주위 환경에 상당히 민감하다. 그래서 광굴절매질의 자기위상공액성질을 이용하여 안정된 간섭패턴을 얻는다. 그리고 원영상은 복원된 홀로그램을 위상 변조한 후, 역푸리에 변환하여 최종적으로 구한다. 제안된 시스템에서는 암호화시에 사용된 무작위 키 영상 정보가 없으면 전혀 복원이 되지 않고, 키 영상을 달리함에 따라 복원되는 홀로그램의 패턴을 달리할 수 있으므로 차별화된 인증 시스템에 활용할 수 있다. 그리고 홀로그램의 성질에 의해 암호화된 영상이 일부 절단되더라도 원래의 영상을 복원할 수 있다.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.395-401
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• 2003

다목적 대형 댐의 건설로 수몰된 과거의 삶의 공간을 20년이 지나서 다시 복원한다는 것은 그곳에 살던 실향민 등에게는 참으로 반가운 소식이다. 본 연구에서는 1980년대 초에 완공된 충주댐으로 인하여 물 속에 잠긴 청풍지구를 수몰이전의 입체 지형 공간적으로 원형복원하기 위한 원격탐사 기법을 적용한 것이다. 비교적 해상도가 좋은 인공위성 사진자료와 댐 수몰이전의 디지털 위성영상 데이터를 수집하고, 수몰직전에 제작된 지형도를 이용하여 위성영상자료의 통합 적용하여 수몰직전의 지형공간정보를 현재시간으로 영상 복원하기 위하여 원격탐사 기법을 적용한 것이다 이를 위하여 지형도에서 추출한 등고선과 현재의 등고선과의 접목을 통하여 청풍 주변지역을 중심으로 당시의 수치표고모형을 생성하였다. 또한 이를 입체적으로 보여주기 위한 투시조감도를 각 방향에서 생성함으로서 수몰이전의 아름다운 모습을 3차원적으로 영상복원 하였다. 또한 좀더 가까이서 수몰마을을 보기 위한 근접비행시뮬레이션 동영상을 제작하여 과거 기억 속의 고향을 영상에서 찾아볼 수 있도록 한 것이다.