• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.588-591
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• 2009

This paper proposes a reversible information hiding method for binary images. A half of pixels in noisy blocks on cover images is candidate for embeddable pixels. Among the candidate pixels, we select compressive pixels by bit patterns of its neighborhood to compress the pixels effectively. Thus, embeddable pixels in the proposed method are compressive pixels in noisy blocks. We provide experimental results using several binary images binarized by the different methods.

• 한국통신학회논문지
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• 제22권1호
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• 전자공학회논문지S
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• 제34S권3호
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• pp.97-107
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• 1997

Image segmentation is teh important step in image infromation extraction for computer vison sytems. Fuzzy clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are derived from the fuzzy c-means (FCM) algorithm. The FCM algorithm uses th eprobabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belongingor compatibility. moreover, the FCM algorithm has considerable trouble above under noisy environments in the feature space. Recently, the possibilistic C-mean (PCM) for solving growing for color image segmentation. In the PCM, the membersip values may be interpreted as degrees of possibility of the data points belonging to the classes. So, the problems in the FCM can be solved by the PCM. The clustering results by just PCM are not smoothly bounded, and they often have holes. So, the region growing was used as a postprocessing. In our experiments, we illustrated that the proposed method is reasonable than the FCM in noisy enviironments.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.605-608
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• 1999

A conventional image coder, such as JPEG, requires not only DCT and quantization but also additional pre-filtering under noisy environment. Since the pre-filtering removes camera noise and improves coding efficiency dramatically, its efficient implementation has been an important issue. Based on well-known noise removal techniques in image processing fields, this paper introduces an efficient scheme by adapting a noise removal procedure to block-based image coders. By using two-dimensional DCT factorization, the proposed image coder has only a modified DCT and a VLC, and performs pre-filtering and quantization simultaneously in the modified DCT operation.

• 비파괴검사학회지
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• 제31권6호
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• pp.665-670
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• 2011

In this paper, a new approach to detect surface cracks from a noisy thermal image in the infrared thermography is presented using an holomorphic characteristic of temperature field in a thin plate under steady-state thermal condition. The holomorphic function for 2-D heat flow field in the plate was derived from Cauchy Riemann conditions to define a contour integral that varies according to the existence and strength of a singularity in the domain of integration. The contour integral at each point of thermal image eliminated the temperature variation due to heat conduction and suppressed the noise, so that its image emphasized and highlighted the singularity such as crack. This feature of holomorphic function was also investigated numerically using a simple thermal field in the thin plate satisfying the Laplace equation. The simulation results showed that the integral image selected and detected the crack embedded artificially in the plate very well in a noisy environment.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.35-41
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• 2018

In this paper, we propose a swarm-based possibilistic c-means(PCM) algorithm in order to overcome the problems of PCM, which are sensitiveness of clustering performance due to initial cluster center's values and producing coincident or close clusters. To settle the former problem of PCM, we adopt a swam-based global optimization method which can be provided the optimal initial cluster centers. Furthermore, to settle the latter problem of PCM, we design an adaptive thresholding model based on the optimized cluster centers that yields preliminary clustered and un-clustered dataset. The preliminary clustered dataset plays a role of preventing coincident or close clusters and the un-clustered dataset is lastly clustered by PCM. From the experiment, the proposed method obtains a better performance than other PCM algorithms on a simulated magnetic resonance(MR) brain image dataset which is corrupted by various noises and bias-fields.

• KIEAE Journal
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• 제3권2호
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• pp.33-36
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• 2003

The influence of the visual information on the sound perception would be considerable. Furthermore, if the sound perception ranges in noisiness or annoyance beyond the loudness, it will depend much more on the shape of the visual information. This paper aims to estimate the influence of the several kinds of visual information on the perception of road traffic noise by means of the psycho-acoustic test method. The findings of present study on the influence of visual information on subjective noise perception are summarized as follows: Presenting visual images of mild and comfortable scenery reduced the noise perception reaction at the less noisy environments not exceeding 65 dB(A). At highly noisy environments exceeding 65 dB(A), however, the noise perception can be reduced by strong image of waterfall. Even eliminating the road traffic image may be helpful. Visual image of waterfall reduced the noise perception at all levels. It is inferred that the road traffic noise perception can be effectively ameliorated by presenting strong and real landscape images at any noisy environment.

• 융합보안논문지
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• 제2권2호
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• pp.99-108
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• 2002

본 연구에서는 실제 야외 환경에서 얻어지는 영상열에서 차영상 기법을 이용하여 침입자를 감지하는 보안 시스템에서 필요한 참고영상 갱신 방안을 제안한다. 제안된 방법은 선별적 참고영상 갱신방법의 영역판별 오류에 의한 영향을 미디언 필터링(Median Filtering)을 이용하여 최소화하였다. 먼저, 연속적으로 들어오는 입력영상과 참고영상의 차영상을 얻어 상향조정된 임계치를 이용하여 이동물체 영역이 제거된 선별적인 임시영상을 생성한다. 그리고 조명의 변화나 이동물체의 외곽에 반응하는 배경물체의 오류를 제거하기 위해 미디언 필터링을 수행함으로써 불규칙적으로 발생하는 밝기변화에 적응할 수 있게 한다. 제안된 방법을 실제 야외 상황에서 얻은 다양한 영상열에 적용한 결과 기존의 참고영상 갱신방법보다 주위 잡음과 무관한 참고영상을 생성한 수 있었다.

• 전자공학회논문지B
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• 제33B권11호
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• pp.72-82
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• 1996

In this paper, newly developed algorithm for enhancing images corrupted by white gaussian noise is proposed. In the method proposed here, image is subdivided into a number of subblocks, and each block is separated into cimponents corresponding to signal and noise subspaces, respectively through the signal subspace method. A clean signal is then estimated form the signal subspace by the adaptive wiener filtering. The decomposition of noisy signal into noise and signal subspaces in is implemented by eigendecomposition of covariance matrix for noisy image, and by performing blockwise KLT (karhunen loeve transformation) using eigenvector. To reduce the perceptual noise level and distortion, wiener filtering is implementd by adaptively adjusting noise level according to activity characteristics of given block. Simulation results show the effectiveness of proposed method. In particular, edge bluring effects are reduced compared to the previous methods.

• 대한전자공학회논문지
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• 제26권8호
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• pp.1238-1246
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• 1989

In this paper, a texture synthesis technique based on the NCAR(non-causal auto-regressive) model and the pyramid structure is proposed. In order to estimate the NCAR model parameters accurately from a noisy texture, the MAP(maximum a posteriori) estimation technique is also employed. In our approach, since the input texture is decomposed into the Laplacian oyramid planes first and then the NCAR model is applied to each plane, we are able to obtain a good synthesized texture even if the texture exhibits some non-random local structure or non-homogenity. The usrfulness of the proposed method is demonstrated with seveal real textures in the Brodatz album. Finally, the 2-dimensional MAP estimation technique can be used to the image restoration for noisy images as well as a texture image synthesis.