• 한국항해항만학회지
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• 제35권4호
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• pp.317-321
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• 2011

In this paper, a foggy-degraded image restoration technique with a physics-based degradation model is proposed for the measurement system. When the degradation model is used for the image restoration, its parameters and a distance from the spreader to the camera have to be previously known. In the proposed image restoration technique, the parameters are estimated from variances and averages of intensities on two foggy-degraded landmark images taken at different distances. Foggy-degraded images can be restored with the estimated parameters and the distance measured by the measurement system. On the basis of the experimental results, the performance of the proposed foggy-degraded image restoration technique was verified.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.27-40
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• 2022

In this paper, the focus on the removal noise in the binary image based on the variational Bayesian method with the Ising model. The observation and the latent variable are the degraded image and the original image, respectively. The posterior distribution is built using the Markov random field and the Ising model. Estimating the posterior distribution is the same as reconstructing a degraded image. MCMC and variational Bayesian inference are two methods for estimating the posterior distribution. However, for the sake of computing efficiency, we adapt the variational technique. When the image is restored, the iterative method is used to solve the recursive problem. Since there are three model parameters in this paper, restoration is implemented using the VECM algorithm to find appropriate parameters in the current state. Finally, the restoration results are shown which have maximum peak signal-to-noise ratio (PSNR) and evidence lower bound (ELBO).

• Journal of applied mathematics & informatics
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• 제38권5_6호
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• pp.519-532
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• 2020

In this paper, we first propose a new total variation-based regularization model for image restoration. We next propose a fixed-point-like method for solving the new image restoration model, and then we provide convergence analysis for the fixed-point-like method. To evaluate the feasibility and efficiency of the fixed-point-like method for the new proposed total variation-based regularization model, we provide numerical experiments for several test problems.

• 대한수학회지
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• 제55권3호
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 추계학술대회
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• pp.60-63
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• 2020

With the advent of deep learning, a lot of attempts have been made in computer vision to substitute deep learning models for conventional algorithms. Among them, image classification, object detection, and image restoration have received a lot of attention from researchers. However, most of the contributions were refined in one of the fields only. We propose a new paradigm of model structure. End-to-end model which we will introduce classifies noise of an image and restores accordingly. Through this, the model enhances universality and efficiency. Our proposed model is an 'One-For-All' model which classifies weather condition in an image and returns clean image accordingly. By separating weather conditions, restoration model became more compact as well as effective in reducing raindrops, snowflakes, or haze in an image which degrade the quality of the image.

• 한국통신학회논문지
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• 제12권2호
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• pp.176-188
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• 1987

본 논문은 역필터링을 이용하여 이동에 의해 흐려진 영상을 복원하는 기법에 관한 논문이다. 적절한 역필터를 설계하기 위하여 저하과정(Degradation Process)을 정확히 모델링하여 그의 역특성을 갖는 필터를 구해내야 한다. 고속으로 이동하는 물체의 영상은 Blurring되는데, 이것은 수학적으로 시간에 대한 영상의 적분으로 모델링될 수 있으며, 공간좌표상 방향성 방형 윈도우(Rectangular Window)를 상승(Convolution)하는 것으로 분석된다. 본 논문에서는 주파수 영역에서 이를 분석하여, 이동방향을 고려한 역 Sinc 함수 특성을 갖는 필터를 이용하여 흐려진 영상을 복원하는 기법을 연구한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.365-367
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• 2008

A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1182-1194
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• 2016

The single image dehazing algorithm in existence can satisfy the demand only for improving either the effectiveness or efficiency. In order to solve the problem, a novel variational framework for single image dehazing based on restoration is proposed. Firstly, the initial atmospheric scattering model is transformed to meet the kimmel's Retinex variational model. Then, the green light component of image is considered as an input of the variational framework, which is generated by the sensitivity of green wavelength. Finally, the atmospheric transmission map is achieved by multi-resolution pyramid reduction to improve the visual effect of the results. Experimental results demonstrate that the proposed method can remove haze effectively with less memory consumption.

• 전자공학회논문지S
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• 제35S권12호
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• pp.77-83
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• 1998

일반적으로 동영상은 물체의 움직임에 의해 움직임 열화를 겪는다. 본 논문의 목적은 이러한 움직임 열화의 해석을 위한 모델을 제시하고 정칙화된 반복 기법을 이용하여 이를 제거하기위한 복원방식을 제안하는 것이다. 제안된 모델에서는 기존의 공간 불변적인 모델의 한계를 극복하기 위하여 움직이는 물체와 정지된 배경과의 경계에서 일어나는 현상을 수학적으로 해석하게 된다. 그리고 복원 과정에서의 객체기반적 처리를 위하여 움직임을 기반으로 하는 영상 분할 기법을 소개하는데, 이 기법은 기존의 연구를 바탕으로 본 연구에 맞도록 응용하여 사용한다. 제안된 모델을 근거로 한 영상복원 기법은 제약조건을 이용한 반복적 방법으로서 사전에 추정된 열화정보를 이용하여 움직임 열화를 제거하개 된다. 제안된 방법의 성능은 실험결과로서 확인할 수 있다.

• 한국컴퓨터정보학회논문지
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• 제10권4호
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• pp.17-27
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• 2005

본 논문에서는 문자인식과 복원을 위한 신경회로망 시스템을 제안한다. 제안하는 시스템은 인식부와 연상부로 구성되었다. 인식부에서는 ART 신경회로망의 인식성능을 개선하기 위해 불필요한 하향틀의 생성과 변화를 제한하여 효과적인 패턴인식이 가능한 모델을 제안하였다. 또한, 한글의 구조적인 특징을 능동적으로 적용할 수 있게 구성된 위치특징 추출 알고리즘을 적용하였다. 연상부에서는 Hopfield 신경회로망으로, 입력된 이미지 패턴의 복원이 가능한 모델을 구성하였다. 제안하는 시스템은 그 성능을 확인하기 위해 각 부분별 실험을 하였다. 그 결과 인식율이 개선되고 복원이 가능함을 보였다.