• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1990년도 추계학술대회
• /
• pp.5-10
• /
• 1990

The object detection capabilities of ultrasonic imaging systems are limited by the ability of the detection process to distinguish the resolved object signals from backscattered speckle noise. It has been shown that the phase component of the Fourier transform of the speckle noise is random. Based on this property. we propose a new algorithm for distinguishing between speckle and specular targets. The proposed algorithm is implemented by taking the Fourier transform of the received signal, low-pass filtering the phase, and taking the inverse Fourier transform of the filtered phase to enhance specular reflectors and reduce speckle in the image. Simulations and experiments using phantoms confirm the algorithm yielding significant reduction of speckle noise.

• 한국전자파학회논문지
• /
• 제15권9호
• /
• pp.856-862
• /
• 2004

유전자 알고리즘을 사용하여 전파 잡음의 통계적 모형(APD: amplitude probability distribution)으로부터 최적파라미터를 추출, 데이터베이스화하는 프로그램을 개발하였다. 제안된 파라미터 추출 방법은 기존의 시행 착오법과 비교하여 추출 시간이 단축되고 추출과정의 자동화가 가능하며 각 파라미터별로 국부적 최적화가 아닌 전역적 최적화를 시행할 수 있다는 장점을 가지고 있다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권12호
• /
• pp.827-833
• /
• 2004

In active noise control (ANC) systems, the error-reduction performance of the conventional Filtered-X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortions in the secondary path such as in the power amplifiers, loudspeakers and transducers. In this paper, a nonlinear FXLMS algorithm with high error-reduction performance is proposed to compensate for undesirable nonlinearities in the secondary-path of ANC systems by employing the inverse Volterra filtering approach. In particular, the proposed approach is based on the utilization of the conventional P-th order inverse approach to nonlinearity compensation in the secondary path of ANC systems. Finally, the simulation results showed that the proposed approach yields a better nonlinearity compensation performance for the ANC systems with a nonlinear secondary path than the conventional FXLMS.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
• /
• pp.222-224
• /
• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• 한국멀티미디어학회논문지
• /
• 제12권1호
• /
• pp.26-30
• /
• 2009

본 논문에서는 로버스트 통계학의 순위 추정을 기반으로 하고 순서통계학의 L-추정자를 이용한 적응 순환 최소 순위(RLR) L-필터를 제안한다. 제안한 RLR-L 필터는 비선형 적응알고리즘을 가진 비선형 적응 필터로서 오차의 분산측정을 최소화하는 관점의 최적 필터로 가변적인 스텝 크기를 가지며 적응한다. 제안한 필터는 영상신호와 같은 비정체 신호나 가우시안 잡음 또는 임펄스 잡음과 같은 비선형 채널에 적합하다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
• /
• pp.49-52
• /
• 2000

This paper is to propose an algorithm to reduce the calculation time to perform the 2-dimensional Discrete Wavelet Transform(2DWT). We call this algorithm as Reduced 2-dimensional Discrete Wavelet Transformation(R2DWT). This algorithm uses a modified Mallat-tree such that in each level, the column transform is performed only with the low-pass filtered row transform result. The resulting number of sub-band regions is 2L＋1, meanwhile the original(2DWT) has 3L＋1 sub-regions, where L is the transform level. To show the proposed algorithm is useful without much loss in SNR(Signal-to-Noise Ratio), we performed experiments with various images. The results showed that above 5:1 in compression ratio, the proposed algorithm has less than 0.SdB difference in SNR from 2DWT with about 25% reduction in calculation time.

• 한국정보통신학회논문지
• /
• 제17권1호
• /
• pp.32-40
• /
• 2013

본 논문에서는 빔포밍과 입사각분석 기반 마스킹을 이용한 다채널 음성개선 알고리즘이 제안된다. 제안된 알고리즘에서는 LCMV 빔포밍을 수행한 후에 입사각 분석을 이용한 멜-주파수 위너필터가 적용되어 잔존하는 잡음을 제거한다. 성능 향상을 위해서 빔포밍의 적응 필터 학습률과 목표 음성 스펙트럼 검출을 위한 입사각 임계치가 최적화된다. 성능 지수로서 PESQ와 출력 SNR이 측정되었으며 실험 결과 제안한 알고리즘이 종전의 최소분산 빔포밍 기법보다 PESQ 관점에서 0.09, 출력 SNR 관점에서 5.75 dB의 성능 향상시킴을 알 수 있었다.

• 한국정보통신학회논문지
• /
• 제21권3호
• /
• pp.629-635
• /
• 2017

본 논문에서는 영상에 첨가된 가우시안 잡음과 임펄스 잡음의 영향을 완화하기 위하여 잡음의 종류에 따라 처리하는 비선형 합성 필터를 제안하였다. 잡음 판단을 통해 국부 마스크의 중심화가 가우시안 잡음으로 판단된 경우, 국부 마스크 내의 표본분산을 이용하여 공간 가중치 필터와 화소 변화에 따른 가중치 필터의 가중치를 다르게 적용하여 처리하고, 임펄스 잡음으로 판단된 경우, 국부 마스크의 잡음 밀도에 따라 국부 히스토그램 가중치 필터와 표준 메디안 필터의 가중치를 다르게 적용하여 처리하는 알고리즘을 제안하였다. 그리고 제안한 필터 알고리즘의 성능을 평가하기 위해 PSNR(peak signal to noise ratio)을 사용하여 기존의 방법들과 제안한 필터 알고리즘을 가우시안 잡음, 임펄스 잡음 및 두 잡음이 혼합된 복합잡음 환경에서 각각 비교하였다.

• Investigative Magnetic Resonance Imaging
• /
• 제20권4호
• /
• pp.215-223
• /
• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2000년도 춘계학술대회논문집
• /
• pp.239-245
• /
• 2000

Adaptive bang-bang control algorithm has been proposed by the authors to improve peak response reduction of building structures under unexpected large earthquake. At the previous research, control performance of the proposed algorithm was experimentally confirmed by using a I-DOF test structure. As an extended research, performance tests on a multi-DOF model structure have been conducted to prove the usefulness of the adaptive bang-bang control algorithm using a hydraulic AMD. It is confirmed that the proposed adaptive bang-bang algorithm is applicable to suppress the vibration of multi-DOF structures subject to severe external excitations.