• Title/Summary/Keyword: Adaptive Enhancement

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Medical Image Enhancement Using an Adaptive Nonlinear Histogram Stretching (적응적 비선형 히스트그램 스트레칭을 이용한 의료영상의 화질향상)

  • Kim, Seung-Jong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.658-665
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    • 2015
  • In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Finally, an adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.

The Realization of Panoramic Infrared Image Enhancement and Warning System for Small Target Detection (소형 표적 탐지를 위한 파노라믹 적외선 영상 향상 장치 및 경보시스템 구현)

  • Kim Ki Hong;Kim Ju Young;Jung Tae Yeon;Jeon Byung Gyoon;Lee Eui Hyuk;Kim Duk Gyoo
    • Journal of Korea Multimedia Society
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    • v.8 no.1
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    • pp.46-55
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    • 2005
  • In this paper, we realize the panoramic infrared warning system to detect the small threaten object and propose the infrared image enhancement method to improve the warning ability of this system. This system composes of the sense head unit, the signal processing unit, and so on. In the proposed system, the sense head unit acquires the panoramic IR image with 360 degree field of view(FOV) by rotating the thermal sensor. The signal processing unit divides panoramic image into four sub-images with 90 degree FOV and computes the adaptive plateau value by using statistical characteristics of each subimage. Then the histogram equalization is performed for each subimage by using the adaptive plateau value. We realize the signal Processing unit by using the DSP and FPGA to perform the proposed method in real time. Experimental results show that the proposed method has better discrimination and lower false alarm rate than the conventional methods in this warning system.

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Vibration Signal Analysis of Running Electric Train using Adaptive Signal Processing (적응신호처리에 의한 주행전기동차의 진동신호해석)

  • 최연선
    • Journal of the Korean Society for Railway
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    • v.2 no.2
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    • pp.13-20
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    • 1999
  • The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

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HF-Band Wireless Power Transfer System with Adaptive Frequency Control Circuit for Efficiency Enhancement in a Short Range (근거리에서 효율 향상을 위해 적응 주파수 제어 회로를 갖는 HF-대역 무선 전력 전송 시스템)

  • Jang, Byung-Jun;Won, Do-Hyun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.11
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    • pp.1047-1053
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    • 2011
  • In this paper, we proposed an HF-band wireless power transfer system with adaptive frequency control circuit for efficiency enhancement in a short range. In general, a wireless power transfer system shows an impedance mismatching due to a reflected impedance, because a coupling coefficient is varied with respect to separation distance between two resonating loop antennas. The proposed method can compensate this impedance mismatching by varying input frequency of a voltage-controlled oscillator adaptively with respect to separation distance. Therefore, transmission efficiency is enhanced in a short distance, where large impedance mismatch occurs. The adaptive frequency circuit consists of a directional coupler, a detector, and a loop filter. In order to demonstrate the performance of the proposed system, a wireless power transfer system with adaptive frequency control circuits is designed and implemented, which has a pair of loop antennas with a dimension of 30${\times}$30 $cm^2$. From measured results, the proposed system shows enhanced efficiency performance than the case without adaptive frequency control.

SPEECH ENHANCEMENT BY FREQUENCY-WEIGHTED BLOCK LMS ALGORITHM

  • Cho, D.H.
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1985.10a
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    • pp.87-94
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    • 1985
  • In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.

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Performance Enhancement of SBC for Voice Signal Using Adaptive Postfiltering at the Medium Bit Rate (중간 전송율에서 적응 포스트 필터링을 이용한 음성용 SBC의 성능 향상)

  • 김원구;이남걸;윤대희;차일환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.2
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    • pp.121-131
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    • 1992
  • In this paper, three methods are studied to enhance the performance of SBC ( Sub-Band Coding )schemes for voice signal at the medium bit rate between 12 kbps and If; kbps, and adaptive postfilteritng using human auditory characteristics Is (Bone at the decoder out put. First, GQMF(Generalized Quadrature Mirror Filter ) Is used instead of QME'((Quadrature MirrorFiltcr ) to have better performance. Second, by adaptive bit allocation to each sub-band, speech quality is enhanced and valuable rate ceding If possible. Third, corriparlson study oS thr: coder performance using APCM(Adaptive Pulse Code ModulatioTi) and ADPCM( Adaptive Differentiai Pulse Code Modulatiori) , Indicates that SB AfCM performance better than the other. Adaptive postfiltering at the decoder output enhances the quality of the coded speech. The two proposed postfiltering methods decrease the noise sufficiently at the expense of the low computational load.

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Vibration Signal Analysis of Running Electric Train using Adaptive Signal Processing (적응신호처리에 의한 주행전기동차의 진동신호해석)

  • 최연선;이봉현
    • Proceedings of the KSR Conference
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    • 1999.05a
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    • pp.143-150
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    • 1999
  • The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study. The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

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Design of Reliable Adaptive Fitter with Fault Tolerance Using DSP (DSP를 이용한 고장허용을 갖는 신뢰 적응 필터 설계)

  • 유동완;이전우;서보혁
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.1
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    • pp.8-13
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    • 2001
  • LMS algorithm has been used for plant identifier and noise cancellation. This algorithm has been researched for performance enhancement of filtering. The design and development of a reliable system has been becoming a key issue in industry field because the reliability of a system is considered as an important factor to perform the system's function successfully. And the computing with reliability and fault tolerance is a important factor in the case of aviation, system communication, and nuclear plant. This paper presents design of reliable adaptive filter with fault tolerance. Generally, redundancy is used for reliability. In this case it needs computing or circuit for voting mechanism, or fault detection. Therefore it has simple computing, and practicality for application. And in this paper, reliability of adaptive filter is analyzed. The effectiveness of the proposed adaptive filter is demonstrated to the case studies of plant identifier and noise cancellation by using DSP.

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A New Least Mean Square Algorithm Using a Running Average Process for Speech Enhancement

  • Lee, Soo-Jeong;Ahn, Chan-Sik;Yun, Jong-Mu;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.3E
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    • pp.123-130
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    • 2006
  • The adaptive echo canceller (AEC) has become an important component in speech communication systems, including mobile station. In these applications, the acoustic echo path has a long impulse response. We propose a running-average least mean square (RALMS) algorithm with a detection method for acoustic echo cancellation. Using colored input models, the result clearly shows that the RALMS detection algorithm has a convergence performance superior to the least mean square (LMS) detection algorithm alone. The computational complexity of the new RALMS algorithm is only slightly greater than that of the standard LMS detection algorithm but confers a major improvement in stability.

Noise Suppression Using Normalized Time-Frequency Bin Average and Modified Gain Function for Speech Enhancement in Nonstationary Noisy Environments

  • Lee, Soo-Jeong;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.1E
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    • pp.1-10
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    • 2008
  • A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.