• Title/Summary/Keyword: adaptive method

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Color Image Enhancement Based on Adaptive Nonlinear Curves of Luminance Features

  • Cho, Hosang;Kim, Geun-Jun;Jang, Kyounghoon;Lee, Sungmok;Kang, Bongsoon
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.15 no.1
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    • pp.60-67
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    • 2015
  • This paper proposes an image-dependent color image enhancement method that uses adaptive luminance enhancement and color emphasis. It effectively enhances details of low-light regions while maintaining well-balanced luminance and color information. To compare the structure similarity and naturalness, we used the tone mapped image quality index (TMQI). The proposed method maintained better structure similarity in the enhanced image than did the space-variant luminance map (SVLM) method or the adaptive and integrated neighborhood dependent approach for nonlinear enhancement (AINDANE). The proposed method required the smallest computation time among the three algorithms. The proposed method can be easily implemented using the field-programmable gate array (FPGA), with low hardware resources and with better performance in terms of similarity.

A Simple Speech/Non-speech Classifier Using Adaptive Boosting

  • Kwon, Oh-Wook;Lee, Te-Won
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.3E
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    • pp.124-132
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    • 2003
  • We propose a new method for speech/non-speech classifiers based on concepts of the adaptive boosting (AdaBoost) algorithm in order to detect speech for robust speech recognition. The method uses a combination of simple base classifiers through the AdaBoost algorithm and a set of optimized speech features combined with spectral subtraction. The key benefits of this method are the simple implementation, low computational complexity and the avoidance of the over-fitting problem. We checked the validity of the method by comparing its performance with the speech/non-speech classifier used in a standard voice activity detector. For speech recognition purpose, additional performance improvements were achieved by the adoption of new features including speech band energies and MFCC-based spectral distortion. For the same false alarm rate, the method reduced 20-50% of miss errors.

Development of Software For Machinery Diagnostics by Adaptive Noise Cancelling Method (1St: Cepstrum Analysis)

  • Lee, Jung-Chul;Oh, Jae-Eung;Yum, Sung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.836-841
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    • 1987
  • Many kinds of conditioning monitoring technique have been studied, so this study has investigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analysis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in oder to identify obviously the physical meaning of ANC. The optimal adaptation gain in adaptive filter is estimated, the performance of ANC according to the change of the signal to noise ratio and convergence of LMS algorithm is considered by simulation. It is verified that cepstral analysis using ANC method is more effective than the conventional cepstral analysis method in bearing fault diagnosis.

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Human Adaptive Device Development based on TD method for Smart Home

  • Park, Chang-Hyun;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1072-1075
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    • 2005
  • This paper presents that TD method is applied to the human adaptive devices for smart home with context awareness (or recognition) technique. For smart home, the very important problem is how the appliances (or devices) can adapt to user. Since there are many humans to manage home appliances (or devices), managing the appliances automatically is difficult. Moreover, making the users be satisfied by the automatically managed devices is much more difficult. In order to do so, we can use several methods, fuzzy controller, neural network, reinforcement learning, etc. Though the some methods could be used, in this case (in dynamic environment), reinforcement learning is appropriate. Among some reinforcement learning methods, we select the Temporal Difference learning method as a core algorithm for adapting the devices to user. Since this paper assumes the environment is a smart home, we simply explained about the context awareness. Also, we treated with the TD method briefly and implement an example by VC++. Thereafter, we dealt with how the devices can be applied to this problem.

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Speech Enhancement Using Level Adapted Wavelet Packet with Adaptive Noise Estimation

  • Chang, Sung-Wook;Kwon, Young-Hun;Jung, Sung-Il;Yang, Sung-Il;Lee, Kun-Sang
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.2E
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    • pp.87-92
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    • 2003
  • In this paper, a new speech enhancement method using level adapted wavelet packet is presented. First, we propose a level adapted wavelet packet to alleviate a drawback of the conventional node adapted one in noisy environment. Next, we suggest an adaptive noise estimation method at each node on level adapted wavelet packet tree. Then, for more accurate noise component subtraction, we propose a new estimation method of spectral subtraction weight. Finally, we present a modified spectral subtraction method. The proposed method is evaluated on various noise conditions: speech babble noise, F-l6 cockpit noise, factory noise, pink noise, and Volvo car interior noise. For an objective evaluation, the SNR test was performed. Also, spectrogram test and a very simple listening test as a subjective evaluation were performed.

Channel-Adaptive Beamforming Method for OFDMA Systems in frequency-Selective Channels (주파수 선택적 채널에서 OFDMA 시스템을 위한 적응 빔포밍 방법)

  • Han Seung Hee;Lee Kyu In;Ahn Jae Young;Cho Yong Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.10C
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    • pp.976-982
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    • 2005
  • In this paper, a channel-adaptive beamforming method is proposed for OFDMA (Orthogonal Frequency Division Multilexing Access) systems with smart antenna, in which the size of a cluster is determined adaptively depending on the frequency selectivity of the channel. The proposed method consists of 4 steps: initial channel estimation, refinement of channel estimates, region-splitting, and computation of weight vector for each region. In the proposed method, the size of a cluster for resource unit is determined adaptively according to a region-splitting criterion. It is shown by simulation that the proposed method shows good performances in both frequency-flat and frequency-selective channels.

Adaptive Wavelet Based Speech Enhancement with Robust VAD in Non-stationary Noise Environment

  • Sungwook Chang;Sungil Jung;Younghun Kwon;Yang, Sung-il
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.4E
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    • pp.161-166
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    • 2003
  • We present an adaptive wavelet packet based speech enhancement method with robust voice activity detection (VAD) in non-stationary noise environment. The proposed method can be divided into two main procedures. The first procedure is a VAD with adaptive wavelet packet transform. And the other is a speech enhancement procedure based on the proposed VAD method. The proposed VAD method shows remarkable performance even in low SNRs and non-stationary noise environment. And subjective evaluation shows that the performance of the proposed speech enhancement method with wavelet bases is better than that with Fourier basis.

A Symbol Synchronization Algorithm With an Adaptive Threshold Establishment Method For OFDM Systems (OFDM시스템을 위한 적응 문턱값 설정방식의 심볼동기화 알고리듬)

  • Song, Dong-Ho;Joo, Chang-Bok
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.6
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    • pp.213-224
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    • 2003
  • The proposed algorithm can always set up the optimal threshold value regardless of channel characteristics using an adaptive threshold establishment method that determines the threshold level according to channel noise power, and then it uses the specially designed training symbols that can make the algorithm's estimation performance be less sensitive to power delay profile variation in a multipath channel. In result, the estimation performance of the proposed technique is less affected by channel characteristic variation.

An Adaptive Contrast Enhancement Method using Dynamic Range Segmentation for Brightness Preservation (밝기 보존을 위한 동적 영역 분할을 이용한 적응형 명암비 향상기법)

  • Park, Gyu-Hee;Cho, Hwa-Hyun;Lee, Seung-Jun;Yun, Jong-Ho;Chon, Myung-Ryul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.57 no.1
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    • pp.14-21
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    • 2008
  • In this paper, we propose an adaptive contrast enhancement method using dynamic range segmentation. Histogram Equalization (HE) method is widely used for contrast enhancement. However, histogram equalization method is not suitable for commercial display because it may cause undesirable artifacts due to the significant change in brightness. The proposed algorithm segments the dynamic range of the histogram and redistributes the pixel intensities by the segment area ratio. The proposed method may cause over compressed effect when intensity distribution of an original image is concentrated in specific narrow region. In order to overcome this problem, we introduce an adaptive scale factor. The experimental results show that the proposed algorithm suppresses the significant change in brightness and provides wide histogram distribution compared with histogram equalization.

Region adaptive motion compensated error coding using extension-interpolation/2D-DCT (확장-보간/2D-DCT 기법을 이용한 영역 적응적인 이동보상 오차의 보호화)

  • 조순재;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.8
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    • pp.1691-1697
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    • 1997
  • This paper presents a new motion compensated error coding method suitable for region based image coding system. Compared with block based conding, the region based coding improves subjective quality as it estimates and compensates 2D (or 3D) translantional, rotational, and scaling motion for each regions. although the region based coding has this advantage, its merit is reduced as bock-DCT (2D-DCT) is used to encode motion-compensated error. To overcome this problem, a new region adaptive motion compensated error coding technique which improver subjective and objective quality in the region boundary is proposed in this paper. In the proposed method, regions with large error are estimated using contour of the regions and contrast between the regions. The regions estiated as those with large error are coded by arbitrarily shaped image segment coding method. The mask information of the coded regions is not transmitted because it is estimated as the same algorithm in the encoder and the decoder. The proposed region adaptive motion conpensated error coding method improves about 0.5dB when it is compared with conventional block based method.

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