• Title/Summary/Keyword: Peak estimation

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Low-Complexity Sub-Pixel Motion Estimation Utilizing Shifting Matrix in Transform Domain

  • Ryu, Chul;Shin, Jae-Young;Park, Eun-Chan
    • Journal of Electrical Engineering and Technology
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    • v.11 no.4
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    • pp.1020-1026
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    • 2016
  • Motion estimation (ME) algorithms supporting quarter-pixel accuracy have been recently introduced to retain detailed motion information for high quality of video in the state-of-the-art video compression standard of H.264/AVC. Conventional sub-pixel ME algorithms in the spatial domain are faced with a common problem of computational complexity because of embedded interpolation schemes. This paper proposes a low-complexity sub-pixel motion estimation algorithm in the transform domain utilizing shifting matrix. Simulations are performed to compare the performances of spatial-domain ME algorithms and transform-domain ME algorithms in terms of peak signal-to-noise ratio (PSNR) and the number of bits per frame. Simulation results confirm that the transform-domain approach not only improves the video quality and the compression efficiency, but also remarkably alleviates the computational complexity, compared to the spatial-domain approach.

Compressive sensing-based two-dimensional scattering-center extraction for incomplete RCS data

  • Bae, Ji-Hoon;Kim, Kyung-Tae
    • ETRI Journal
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    • v.42 no.6
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    • pp.815-826
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    • 2020
  • We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

The Sensitivity Analysis of Parameters of Urban Runoff Models due to Variations of Basin Characteristics (I) - Development of Sensitivity Analysis Method - (유역특성 변화에 따른 도시유출모형의 매개변수 민감도분석(I) -민감도분석방법의 개발-)

  • Seo, Gyu-U;Jo, Won-Cheol
    • Journal of Korea Water Resources Association
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    • v.31 no.3
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    • pp.243-252
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    • 1998
  • In this study, the new dimensionless values were defined and proposed to determine the parameters of urban runoff models based on the relative sensitivity analysis. Also, the sensitivity characteristics of each parameter were investigate. In order to analyze the parameter sensitivities of each model, total runoff ratio, peak runoff ratio, runoff sensitivity ratio, sensitivity ratio of total runoff, and sensitivity ratio of peak runoff were defined. $$Total\;runoff\;ratio(Q_{TR})\;=\;\frac{Total\;runoff\;of\;corresponding\;step}{Maximum\;total\;runoff}$$$$Peak\;runoff\;ratio(Q_{PR})\;=\;\frac{Peak\;runoff\;of\;corresponding\;step}{Maximum\;peak\;runoff}$$$$Runoff\;sensitivity\;ratio(Q_{SR})\;=\;\frac{Q_{TR}}{Q_{PR}}$$ And for estimation of sensitivity ratios based on the scale of basin area, rainfall distributions and rainfall durations in ILLUDAS & SWMM, the reasonable ranges of parameters were proposed.

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Development of Blood Pressure Estimation Methods Using The PPG and ECG Sensors (PPG 및 ECG 센서를 이용한 혈압추정 기법 개발)

  • Park, Hyun-Moon;Lee, Jung-Chul;Hwang, Tae-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.6
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    • pp.1257-1264
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    • 2019
  • The traditional cuff-based method for BP(Blood Pressure) measurement is not suitable for continuous real-time BP measurement techniques. For this reason, the previous studies estimated various blood pressures by fusion with the electrocardiography (ECG) and photoplethysmogram (PPG) sensor signals. However, conventional techniques based on PPG bio-sensing measurement face many challenging issues such as noisy supply fluctuation, small pulsation, and drifting non-pulsatile. This paper proposed a novel BP estimation methods using PPG and ECG sensors, which can be derived from the relationship between PPG and ECG using PTT(Pulse Transit Time) and PWV(Pulse Wave Velocity). Unlike conventional height ratio features, which are extracted on the basis of the peaks in the PPG and ECG waveform. The proposed method can be reliably obtained even if there are missing peaks among the sensed PPG signal. The increased reliability comes from periodical estimation of the peak-to-peak interval time using ECG and PPG. After 250,000 times trials of the blood pressure measurement, the proposed estimation technique was verified with the accuracy of ±28.5% error, compared to a commercialized BP device.

Fast Disparity Estimation Method Considering Temporal and Spatial Redundancy Based on a Dynamic Programming (시.공간 중복성을 고려한 다이내믹 프로그래밍 기반의 고속 변이 추정 기법)

  • Yun, Jung-Hwan;Bae, Byung-Kyu;Park, Se-Hwan;Song, Hyok;Kim, Dong-Wook;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.10C
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    • pp.787-797
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    • 2008
  • In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.

MPEG-4 to H.264 Transcoding (MPEG-4에서 H.264로 트랜스코딩)

  • 이성선;이영렬
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.275-282
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    • 2004
  • In this paper, a transcoding method that transforms MPEG-4 video bitstream coded in 30 Hz frame rate into H.264 video bitstream of 15 Hz frame rate is proposed. The block modes and motion vectors in MPEG-4 is utilized in H.264 for block mode conversion and motion vector (MV) interpolation methods. The proposed three types of MV interpolation method can be used without performing full motion estimation in H.264. The proposed transcoder reduces computation amount for full motion estimation in H.264 and provides good quality of H.264 video at low bitrates. In experimental results, the proposed methods achieves 3.2-4 times improvement in computational complexity compared to the cascaded pixel-domain transcoding, while the PSNR (peak signal to noise ratio) is degraded with 0.2-0.9dB depending on video sizes.

Fast block matching algorithm for constrained one-bit transform-based motion estimation using binomial distribution (이항 분포를 이용한 제한된 1비트 변환 움직임 예측의 고속 블록 정합 알고리즘)

  • Park, Han-Jin;Choi, Chang-Ryoul;Jeong, Je-Chang
    • Journal of Broadcast Engineering
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    • v.16 no.5
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    • pp.861-872
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    • 2011
  • Many fast block-matching algorithms (BMAs) in motion estimation field reduce computational complexity by screening the number of checking points. Although many fast BMAs reduce computations, sometimes they should endure matching errors in comparison with full-search algorithm (FSA). In this paper, a novel fast BMA for constrained one-bit transform (C1BT)-based motion estimation is proposed in order to decrease the calculations of the block distortion measure. Unlike the classical fast BMAs, the proposed algorithm shows a new approach to reduce computations. It utilizes the binomial distribution based on the characteristic of binary plane which is composed of only two elements: 0 and 1. Experimental results show that the proposed algorithm keeps its peak signal-to-noise ratio (PSNR) performance very close to the FSA-C1BT while the computation complexity is reduced considerably.

A Motion Vector Re-Estimation Algorithm for Image Downscaling in Discrete Cosine Transform Domain (이산여현변환 공간에서의 영상 축소를 위한 움직임 벡터 재추정)

  • Kim, Woong-Hee;Oh, Seung-Kyun;Park, Hyun-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.5
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    • pp.494-503
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    • 2002
  • A motion vector re-estimation algorithm for image downscaling in discrete consine transform domain is presented. Kernel functions are difined using SAD (Aum of Absolute Difference) and edge information of a macroblock. The proposed method uses these kernel functions to re-estimate a new motion vector of the downscaled image. The motion vectors from the incoming bitstream of transcoder are reused to reduce computation burden of the block-matching motion estimation, and we also reuse the given motion vectors. Several experiments in this paper show that the computation efficiency and the PSNR (Peak Signal to Noise Ratio) and better than the previous methods.

Constrained NLS Method for Long-term Forecasting with Short-term Demand Data of a New Product (제약적 NLS 방법을 이용한 출시 초기 신제품의 중장기 수요 예측 방안)

  • Hong, Jungsik;Koo, Hoonyoung
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.1
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    • pp.45-59
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    • 2013
  • A long-term forecasting method for a new product in early stage of diffusion is proposed. The method includes a constrained non-linear least square estimation with the logistic diffusion model. The constraints would be critical market informations such as market potential, peak point, and take-off. Findings on 20 cases having almost full life cycle are that (i) combining any market information improves the forecasting accuracy, (ii) market potential is the most stable information, and (iii) peak point and take-off information have negative effect in case of overestimation.

Comparison and analysis of peak flow by Areal Reduction Factor (면적감소계수에 따른 첨두유량의 비교연구)

  • Baek, Hyo-Sun;Lee, De-Young;Kang, Young-Buk;Choi, Han-Kuy
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.1798-1802
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    • 2007
  • The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation.The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall.The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

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