• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.407-409
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• 2021

Under the influence of the 4th industrial revolution, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. Digital images may generate noise due to various reasons, and may affect various systems such as image recognition and classification and object tracking. To compensate for these shortcomings, we propose an image restoration algorithm based on pattern information of non-noise pixels. According to the distribution of non-noise pixels inside the filtering mask, the proposed algorithm switched the filtering process by dividing the interpolation method into a pattern that can be applied, a pattern based on region division, and a randomly arranged pixel pattern. preserves and restores the image. The proposed algorithm showed superior performance compared to the existing impulse noise removal algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

In this paper, we analyze geometrical relations of 3D shape reconstruction from 2D images taken under anne projection. The purpose of this research is to contribute to more accurate 3-D reconstruction under noise distribution by analyzing geometrically the 2D to 3D relationship. In situation for no missing feature points (FPs) or no noise in 2D image plane, the accurate solution of 3D shape reconstruction is blown to be provided by Singular Yalue Decomposition (SVD) factorization. However, if several FPs not been observed because of object occlusion and image low resolution, and so on, there is no simple solution. Moreover, the 3D shape reconstructed from noise-distributed FPs is peturbed because of the influence of the noise. This paper focuses on analysis of geometrical properties which can interpret the missing FPs even though the noise is distributed on other FPs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.4-5
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• 2016

최근 현실 세계의 기반 위에 가상의 정보를 증강하여 사용자와 상호작용하며 즐기는 증강 현실 컨텐츠가 대중들에게 많은 인기를 얻고 있다. 이러한 증강 현실 콘텐츠는 현실 세계를 기반으로 한다는 점에서 실제의 3차원 공간을 정확하게 복원하는 것이 중요하다. 초기의 3차원 복원 방법으로 RGB-D 카메라를 이용한 KinectFusion 방법이 제안되었고 많은 연구자들에 의해 다루어지고 있다. 하지만 기존의 방법은 시간이 흐름에 따라 누적되는 오차에 의해 3차원 모델이 정확하게 복원되지 않는 객체 표류 문제가 발생한다. 이러한 문제는 깊이 카메라 센서의 잡음 때문에 정확하지 않은 표면 법선 벡터가 계산되는 것에 기인한다. 본 논문에서는 이러한 문제를 해결하기 위해 잡음에 강건한 표면 법선 벡터를 계산하는 방법을 제안한다. 실험결과에서는 기존의 방법과 비교하여 제안하는 방법이 절대 궤적 오차 (absolute trajectory error)가 감소하는 것을 확인 했고 카메라 궤적이 정확하게 예측되는 것을 확인할 수 있었다.

• Annual Conference of KIPS
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• 2004.11a
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• pp.473-476
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• 2004

본 논문에서는 프라이버시를 침해 하지 않는 데이터 마이닝에 대해 다룬다. 방대한 데이터에서 유용한 정보를 추출하는 데이터 마이닝분야에서 데이터로부터 프라이버시 보존의 중요성이 부각되고 있다. 그래서 프라이버시의 침해를 막기 위한 방법으로 실제 데이터를 사용하지 않고 잡음이 들어간 데이터를 사용한다. 그리고 프라이버시를 침해하지 않기 위해 잡음이 들어간 데이터로부터 데이터의 확률 밀도 함수(PDF)만을 복원한다. 이렇게 복원된 확률 밀도 함수만을 이용하여 데이터 마이닝기술, 예를 들면 분류화에 곧바로 적용함으로써 프라이버시를 보존하는 것이다. 하지만 분류화에 사용되는 데이터의 1차원적인 확률 밀도 함수만 가지고는 군집화에 사용하기가 부적절하다. 따라서 본 논문에서는 군집화를 하기 위해 잡음이 들어간 데이터로부터 결합 확률 밀도 함수(Joint PDF)를 복원하고, 복원된 결합 확률 밀도 함수만 가지고 군집화를 할 수 있는 방법을 다룬다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.150-156
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• 2007

Noise is generated by several causes, when signal is processed. Hence, it generates error in the process of data transmission and decreases recognition ratio of image and speech data. Therefore, after eliminating those noises, a variety of methods for reconstructing the signal have been researched. Recently, wavelet transform which has time-frequency localization and is possible for multiresolution analysis is applied to many fields of technology. Then threshold-and correlation-based methods are proposed for removing noise. But, conventional methods accept a lot of noise as an edge and are impossible to remove the additive white Gaussian noise (AWGN) and the impulse noise at the same time. Therefore, in this paper we proposed new wavelet-based algorithm for reconstructing degraded signal by noise and compared it with conventional methods.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.55-62
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• 2023

Radio waves must pass through the unstable atmosphere for successful wireless data transmission from space to ground stations. Data link algorithms required by the International Space Data Systems Advisory Committee (CCSDS) must be capable of detecting and resynchronizing cryptographic and receiver-side errors. However, error recovery is not part of the CCSDS requirements. This paper proposes an algorithm that enables robustness and error recovery against various noises. We experimented with environments such as Gaussian, Salt, Pepper, and S&P noise through noise reduction filters, filters that improve sharpness, and EDSR. In addition, we compare similar algorithms SES Alarmed and DSES Alarmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.121-126
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• 2009

Plane-based computational integral imaging (CIIR) provides the reconstruction of depth-dependent 3D plane images. However, it has problem degrading the resolution of reconstructed images due to the artifact noise according to the depth. In this paper, to overcome this problem, a signal model for plane-based CIIR is explain. Also the compensation process is introduced to remove the noise caused from CIIR. Computational experiments show that we analyze the characteristics of noise in the reconstructed image of 2D Gaussian image and the high-resolution images can be obtained by using the compensation process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10C
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• pp.605-613
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• 2011

In most digital communication systems over the noisy channel, some form of forward error correction scheme is employed for reliable communications. If one wants to recover the transmitted message without any knowledge of the error correcting codes employed, it is of utmost importance to figure out and reconstruct the error correcting codes. In this paper, we propose two algorithms of reconstructing linear cyclic codes from the corrupted received bit sequence, one for general linear binary cyclic codes and the other for Reed-Solomon codes. For two algorithms, we ran computer simulations and the performances are shown to be superior to those with the conventional LWM method.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.271-280
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• 2004

This paper presents a new iterative image restoration algorithm with removal of boundary/object-oriented ringing, The proposed method is based on CGM(Conjugate Gradient Method) iterations with inter-wavelet shrinkage. The proposed method provides a fast restoration as much as CGM, while having adaptive do-noising and do-ringing by using wavelet shrinkage. In order to have effective do-noising and do-ringing simultaneously, the proposed method uses a space-dependent shrinkage rule. The improved performance of the proposed method over more traditional iterative image restoration algorithms such as LR(Lucy-Richardson) and CGM in do-noising and do-ringing is shown through numerical experiments.