• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.573-578
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• 2014

In this letter, we propose a noise reduction method for use in magnetic resonance images that is based on non-local mean and guided image filters. Our method consists of two phases. In the first phase, the guidance image is obtained from a noisy image by using an adaptive non-local mean filter. The spread of the kernel is adaptively by controlled by implementing the concept of edgeness. In the second phase, the noisy images and the guidance images are provided to the guided image filter as input in order to produce a noise-free image. The improved performance of the proposed method is investigated by conducting experiments on standard datasets that contain magnetic resonance images. The results show that the proposed scheme is superior over the existing approaches.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.37-41
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• 2002

In this paper, we made shorter EDT(early decay time) of room reverberation curve using multiple-channel. The speech signal was processed inverse filtering with full-band and sub-band in the basis MINT, and then the multiple-channel adaptive filters were used LMS (Least Mean Square) and NLMS (Normalized Least Mean Square) algorithm. Experimental results, we could get 1/3 of time reduction at 20dB level in the reverberation curve using full-band NLMS when two microphones were used. Also, it is shown that the speech articulation was improved 80% from the test listeners with the speech, which was to shorten EDT by MINT in the subjective assessments using real room impulse response.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1226-1237
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• 1993

For data transmission over strictly band-limited non-ideal channels, different types of filters with arbitrary responses are needed. In this paper. we proposed two efficient techniques for the design of such FIR filters whose response is specified in either the time or the frequency domain. In particular when a fractionally-spaced structure is used for the transceiver, these filters can be efficiently designed by making use of characteristics of oversampling. By using a minimum mean-squared error criterion, we design a fractionally-spaced FIR filter whose frequency response can be controlled without affecting the output error. With proper specification of the shape of the additive noise signals, for example, the design results in a receiver filter that can perform compromise equalization as well as phase splitting filtering for QAM demodulation. The second method ad-dresses the design of an FIR filter whose desired response can be arbitrarily specified in the frequency domain. For optimum design, we use an iterative optimization technique based on a weighted least mean square algorithm. A new adaptation algorithm for updating the weighting function is proposed for fast and stable convergence. It is shown that these two independent methods can be efficiently combined together for more complex applications.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2592-2594
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• 2002

본 논문에서는 GSC(Generalized Sidelobe Canceller)를 기초로 새로운 부밴드 광대역 적응 빔포밍 구조를 제안하였다. 일반적으로 여러개의 필터계수를 갖는 광대역 빔포밍에서는 그 필터길이가 커짐에 따라 많은 계산량을 필요로 하고 그 성능이 감소한다는 단점이 있었다. 이러한 단점을 보완하기 위해 부밴드 필터구조를 이용함으로써 전밴드 필터구조에서보다 더 낮은 계산량과 그 pre-whitening 효과로 그 성능이 향상되었다. 부밴드 필터뱅크 구조에서 광대역 적응 빔포밍이 수행될 때 NLMS(Normalized Least Mean Squares) 적응 알고리즘을 이용하여 GSC의 수렴성능을 검증하였고, 각각의 부밴드 적응필터에서 MSE를 독립적으로 최소화시키는 적응 메카니즘을 사용하여 추정하였다. 모의실험을 통하여 제안한 부밴드 필터구조가 전밴드 구조에서보다 수렴성능이 더 우수함을 검증하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1319-1324
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• 2013

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the target and candidate image. However, it is sensitive to the noises due to objects or background having similar color distributions. In addition, occlusion by another object often causes a face region to change in size and position although a face region is a critical clue to perform face recognition or compute face orientation. We assume that depth and color are effective to separate a face from a background and a face from objects, respectively. From the assumption we devised a bilateral filter using color and depth and incorporate it into the mean-shift algorithm. We demonstrated the proposed method by some experiments.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.149-157
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• 2012

In this paper, the performance of the sequential filter for a space debris collision management system is analyzed by using the flight data of KOMPSAT-2. To analyze the performance of the sequential filter, the results of batch filter used in the orbit determination system of the KOMPSAT-2 ground station is used as reference data. The overlap method is also used to evaluate the orbit accuracy. This paper shows that the orbit determination accuracy of the sequential filter is similar to that of the KOMPSAT-2 ground station, but dissimilar characteristics exist due to the filter difference. In addition, it is also shown that the orbit determination accuracy is order of 1m root mean square by using 30 hour GPS navigation solutions and 6 hour comparison period for the overlap method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.163-168
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• 2009

In this paper, We proposed the efficient method of cleaning impulse noise using mean shift segmentation. This method do its job for the pixel which is identified as impulse noise using mean shift segmentation instead of all pixel of image by the existing method. we found that the quality of image is improved by measuring the sum of square error in result image and impulse noise is cleaned efficiently by doing experiment.

• Korean Journal of Optics and Photonics
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• v.21 no.1
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• pp.21-25
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• 2010

In this paper, in order to enhance the image reconstruction performance of white light scanning interferometry(WLI), we demonstrate the scattered point noise filtering performance of post-processing methods. Median filtering is similar to using an averaging filter. Because the median value is less sensitive than the mean to extreme values, the median filter can remove the scattered point noise from a height-map without significantly reducing the sharpness of the image. In several specific cases, however, the median filter can't remove the scattered point noise. Therefore, we propose a comparative mean filter that uses order-statistic filtering and the mean of the neighborhood pixels. The performance is demonstrated by measuring an array of metal solder balls fabricated on PCB. The proposed method reduced the noise pixels by 4.4 percent.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.88-95
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• 1999

Stack filters are a class of digital nonlinear filters with excellent properties for signal restoration. Unfortunately, present algorithms for designing stack filters with large window size are limited in applications by their computational overhead and serial nature. In this paper, new, highly-parallel algorithm is developed for determining a stack filter which minimizes the mean absolute error criterion. It retains the iterative nature of the present adaptive algorithm, but significantly reduces the number of required to converge to an optima filter. A proof is also give that the proposed algorithm converges to an optimal stack filter.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.23-32
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• 1999

This paper presents a stochastic convergence analysis of LMS algorithm and VS-LMS algorithm for IIR filters using equation error formulation. Under the assumption that the signal is white Gaussian, theoretical equations that characterize the mean and mean-squared behaviors of the algorithms are derived. Computer simulation results show fairly good agreements between the theoretical and the empirical behaviors of the algorithms.