• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.247-251
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• 2001

영상을 처리하는 과정에서 광학시스템과 전기시스템의 특성으로 인해 흐려지고 잡음으로 훼손된 영상을 복원하는 경우에 일반적으로 정칙화 반복복원방법이 사용된다. 기존의 방법은 영상의 국부적인 특성을 고려하지 않고 영상전체에 일률적으로 정칙화 연산자를 사용함으로써 윤곽부분에서는 리플잡음을 초래하고 평면부분에서도 잡음증폭을 피할 수 없으며, 또한 시각적으로 효율적이지 못한 면이 있다. 본 논문에서는 이러한 문제점을 개선하기 위하여, 영상의 국부적인 특성을 고려하여 적응 정칙화 파라메타와 적응 정칙화 연산지를 사용하여 평면영역과 윤곽영역의 방향특성에 따라 적응적으로 처리하는 반복복원방법을 제안한다. 제안한 방법은 기존의 방법과 비교하여 평면영역에서의 잡음 평활화가 개선되고 시각적으로 중요한 윤곽부분 복원에 효율적임을 실험결과를 통해 알 수 있었으며 ISNR 면에서도 우수하였다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.407-410
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• 2000

본 논문에서는 3차원 웨이블릿 부호화 방식으로 압축된 영상 시퀸스를 정칙화 기반 영상복원 방법으로 후처리하는 알고리듬을 제안한다. 우선, 웨이블릿 압축 시스템을 적절한 영상 열화 시스템으로 모델화한다. 그리고, 시간축에 관하여 프레임 간의 같은 위치에 있는 각 픽셀에 대하여 복원을 수행한다. 그 다음으로 2차원 영상 신호에 대하여 복원을 수행하는데. 즉 웨이블릿 변환 계수 정보를 이용하여 영상 및 시간 정보를 여러 스케일의 에지로 분류한 다음, 에지의 방향에 따른 적응적인 제약조건을 사용한다. 이는 각각의 에지 방향에 적합한 고주파 성분을 유지하고, 신호의 각 특성에 적합한 적응적인 정칙화 매개변수를 적용한다. 마지막으로 시간 축에서의 복원과 그것에 이어지는 적응적인 공간 복원에 대한 실험 결과를 보여준다.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.862-867
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• 2006

To restore image degraded by blur and additive noise in the optical and electrical system, a regularized iterative restoration is used. A regularization operator is usually applied to all over the image without considering the local characteristics of image in conventional method. As a result, ringing artifacts appear in edge regions and the noise is amplified in flat regions. To solve these problems we propose an adaptive regularization iterative restoration considering the characteristic of edge and flat regions using directional regularization operator. Experimental results show that the proposed method suppresses the noise amplification in flat regions, and restores the edge more sharply in edge regions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1588-1595
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• 2000

To restore image degraded by out-of-focus blur and additivie noise a regularized iterative restoration is used. In concentional method, regularization is usually applied to all over the image without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solve this problem we propose an adaptive regularization iterative restoration using directional regularization operator considering edges in four directions and the regularization operator with on direction for flat regions. We verified that the proposed method show better results in the suppression of the noise amplification in flat regions, and introduced less ringing artifacts in edge regions. As a result it showed visually better image and improved better ISNR further than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.91-99
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• 1994

We proposed the regularized iterative restoration method considering relaxation parameter and regularization paramenter in order to restore the noisy motion-blurred images. We used (i-H) as a regularization operator and these two kinds of constraints were applied while conventional regularization iterative restoration method proposed by Jan Biemond et al used the 2-D Laplacian filter and a predetermined regularization parameter value and relaxation parameter to 1. Through the experimental results, we showed better results compared with those by a conventional method and or regularized iterative restoration method just considering only a regularization parameter. These two kinds of constratints have good effects when applied into the regularized iterative restoration method for noisy motion-blurred images.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.399-404
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• 2002

To restore image degraded by motion blur and additive noise, it is very difficult. In conventional restoration method, regularization is usually applied to all over the image without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solve this problem we propose an adaptive restoration method using directional regularization operator considering edges and the regularization operator with no direction for flat regions. We verified that the proposed method showed better results in the resolution. As a result it showed visually better image and improved better ISNR further than the conventional methods.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.415-418
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• 2000

렌즈의 초점이 맞지 않아 흐려지고 잡음으로 훼손된 영상을 복원하는 경우에 일반적으로 정칙화 반복복원방법이 사용된다. 기존의 방법은 영상의 국부적인 특성을 고려하지 않고 영상전체에 일률적으로 정칙화를 행함으로써 윤곽부분에서는 리플잡음을 초래하고 평면부분에서도 잡음중폭을 피할 수 없으며, 또한 시각적으로 효율적이지 못한 면이 있다. 이러한 문제점을 개선하기 위하여, 본 논문에서는 영상을 방향이 없는 평면영역과 4가지 방향을 갖는 윤곽영역으로 나누어, 윤곽방향을 고려한 방향성 정칙화 연산자를 사용하여 평면영역과 윤곽영역의 방향특성에 따라 적응적으로 처리하는 반복복원방법을 제안한다. 제안한 방법은 기존의 방법과 비교하여 평면영역에서의 잡음 평활화가 개선되고 시각적으로 중요한 윤곽부분 복원에 효율적임을 실험결과를 통해 알 수 있었으며 ISNR 면에서도 우수하였다.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.1-6
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• 2009

It is very difficult to restore the images degraded by motion blur and additive noise. In conventional methods, regularization usually applies to all the images without considering local characteristics of the images. As a result, ringing artifacts appear in the edge regions and noise amplification is in the flat regions, as well. To solve these problems, we propose an adaptive iterative regularization method, using the way of regularization operator considering edge directions. In addition, we suggest an adaptive regularization parameter and an relaxation parameter. In conclusion, We have verified that the new method shows the suppression of the noise amplification in the flat regions, also does less ringing artifacts in the edge regions. Furthermore, it offers better images and improves the quality of ISNR, comparing with those of conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.39-44
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• 2004

The three-dimensional (3D) wavelet transform with motion compensation is suitable for very high quality video coding due to both spatial and temporal decorrelations. However, it still suffers from image degradation such as ringing artifact and afterimage because of the loss of high frequency components by quantization. This paper proposes an iterative regularized enhancement of the motion-compensated 3D wavelet coded video. We also propose the adaptive implementation of the constraints for the regularization. It selectively suppresses the high frequency component along only the corresponding edge direction.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.139-146
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• 1998

This paper proposes a regularized iterative image restoration using method of conjugate gradient considering a priori information. Compared with conventional regularized method of conjugate gradient, this method has merits to prevent the artifacts by ringing effects and the partial magnification of the noise in the course of restoring the image degraded by blur and additive noise. Proposed method applies the constraints to accelerate the convergence ratio near the edge portions, and the regularized parameter suppresses the magnification of the noise. As experimental results, I show the superior convergence ratio and the suppression by the artifacts of the proposed method compared with conventional methods.