• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.487-491
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• 2009

The inverse halftoning is processing to restore the image made binary to former step image. There are smoothing and gaussian filtering in the technique so far. However, there are still a lot of insufficient points in past inverse halftoning. The removal of the noise and the edge enhansment are closely related in inverse halftoning. It is difficult to do both the noise rednctiom and the edge enhansment in high accuracy at the same time in the technique so far. The technique that can achieve both the removal of the noise and the emphasis of Edge at the same time is expected as future tasks. Then, it was tried to apply the Kalmann filtering to inverse halftoning. In the actual experiment, the effectiveness of the application of the Kalmann filtering to inverse halftoning comparing it with the technique so far was shown.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.547-550
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• 2001

Through matched filtering synthetic aperture radar (SAR) produces high-resolution imagery from data collected by a relative small antenna. While the impulse response obtained by the matched filter approach produces the best achievable signal-to-noise ratio, large sidelobes must be reduced to obtain higher-resolution SAR images. So, many enhancement methods of SAR imagery have been proposed. As a deconvolution method, the phase-extension inverse filtering is based on the characteristics of the matched filtering used in SAR imaging. It improves spatial resolution as well as effectively suppresses the sidelobes with low computational complexity. In the phase-extension inverse filtering, the impulse response is obtained from simulation with a point target. But in a real SAR environment, for example ERS-1, the impulse response is distorted by many non-ideal factors. So, in the phase-extension inverse filtering for a real SAR processing, the magnitudes of the frequency transfer function have to be compensated to produce more desirable results. In this paper, an estimation method to obtain a more accurate impulse response from a real SAR image is studied. And a compensation scheme to produce better performance of the phase-extension inverse filtering is also introduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.113-122
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• 2016

In this paper, we suggest a approach which comprises fast Fourier transform inversion by wavelet noise attenuation. It represents an inverse filtering by adopting a factor into the Wiener filtering, and the optimal factor is chosen to minimize the overall mean squared error. in order to apply the Wiener filter, we have to compute the power spectrum of original image from the corrupted figure. Since the Wiener filtering contains the inverse filtering process, it expands the noise when the blurring filter is not invertible. To remove the large noises, the best is to remove the noise using wavelet threshold. Wavelet noise attenuation steps are consisted of inverse filtering and noise reduction by Wavelet functions. experimental results have not outperformed the other methods over the overall restoration performance.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.151-158
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• 2004

In this paper, an inverse filtering technique for the digital filter model is proposed. This technique enables us to obtain a stable non-causal m inverse filter by transforming (approximating) it to a causal stable inverse system. In practice, a causal FIR approximation to this inverse filter is proposed. It can be shown that the impulse response of the inverse filter for all-pass systems is simply the mirror image of the impulse response for the system. Specially, due to this symmetric property of the impulse response of all-pass systems, the proposed technique is more useful for all-pass systems than other systems. In order to illustrate the proposed inverse filtering technique, four examples are presented. Two of them are for all-pass filters. The other two examples are for IIR and FIR filters. Also, computer simulations demonstrate that the proposed technique works very well.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.29-36
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• 2004

In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theory is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

• Journal of the Korean Society of Radiology
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• v.2 no.4
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• pp.33-40
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• 2008

Images acquired by a digital X-ray imaging system are inherently degraded due to system degradation process and additive noise sources. The system degradation in image quality is typically described as the system response function characterized by the modulation transfer function (MTF) and the noise term described as the noise power spectrum (NPS). In this case, we can restore the blur image as close as possible to the original image by using modified filtering designed for digital imaging system, as we know more precisely about the MTF and the NPS. In this paper, by performing simulation, we tried to restore blurred images taken from a digital X-ray imaging system based upon conventional filtering techniques such as a direct-inverse filtering, limited-inverse filtering, or a Wiener filtering, and evaluated the characteristics of the image restoration.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.4
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• pp.24-29
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• 1999

In this paper, a simple contour-preserving filtering algorithm is proposed. The goal of the contour-preserving filtering method is to remove noise ad granularity as the preprocessing for the image segmentation procedure. Our method finds edge map and separates the image into the edge region and the non-edge region using this edge map. For the non-edge region, typical smoothing filters could be used to remove the noise and the small areas during the segmentation procedure. The result of simulation shows that our method is slightly better than the typical methods such as the median filtering and gradient inverse weighted filtering in the point of view of analysis of variance (ANOVA).

• The Journal of the Acoustical Society of Korea
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• v.5 no.3
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• pp.5-12
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• 1986

음성 신호 처리분야에서 고속이며 정확히 기본 주파수를 추출하는 방법은 중요하며, 이를 위한 많은 연구가 제안되어 왔다. 이러한 방법들은 보통 성도의 방해를 제거한 후에 기본 주파수를 검출하기 때문에 지금까지는 처리과정이 복잡하다. 우리는 그러한 과정을 간단히 처리할 수 ldt는 inverse rate type filtering 법을 제안하였다. 제안된 방법은 유한 길이의 정수 계산이고 덧셈과 뺄셈으로 처리될 수 있기 때문에 범용 마이크로 컴퓨터에 의해서도 실시간 처리를 할 수 있게 된다.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.73-80
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• 2004

In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theorr is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.3
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• pp.20-25
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• 1980

A singular value decomposition (SVD) pseudo-inversion method has been applied to the image reconstruction from projections. This approach is relatively unknown and differs from conventionally used reconstructioll methods such as the Foxier convolution and iterative techniques. In this paper, two SVD pseudo-inversion methods have been discussed for the search of optimum reconstruction and restoration, one using truncated inverse filtering, the other scalar Wiener filtering. These methods partly overcome the ill-conditioned nature of restoration problems by trading off between noise and signal quality. To test the SVD pseudo-inversion method, simulations were performed from projection data obtained from a phantom using truncated inversefiltering. The results are presented together with some limitations particular to the applications of the method to the general class of 3-D image reconstruction and restoration.