• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1613-1631
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• 2011

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised that consists of three main components, i.e., stereo attention predictor (SAP), depth variation (DV), and stereo distortion predictor (SDP). Visual attention is modeled based on entropy and inverse contrast to detect regions or objects of interest/attention. Depth variation is fused into the attention probability to account for the amount of changed depth in distorted stereo images. Finally, the stereo distortion predictor is designed by integrating distortion probability, which is based on low-level human visual system (HVS), responses into actual attention probabilities. The results show that regions of attention are detected among the visually significant distortions in the stereo image pair. Drawbacks of human visual sensitivity based picture quality metrics are alleviated by integrating visual attention and depth information. We also show that positive correlation with ground-truth attention and depth maps are increased by up to 0.949 and 0.936 in terms of the Pearson and the Spearman correlation coefficients, respectively.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.300-306
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• 2012

An image attention model and its application to image quality assessment are discussed in this paper. The attention model is based on rarity quantification, which is related to self-information to attract the attention in an image. It is relatively simpler than the others but results in taking more consideration of global contrasts between a pixel and the whole image. The visual attention model is used to develop a local distortion predictor, named color visual differences predictor (CVDP), in color images in order to effectively detect luminance and color distortions.

• ETRI Journal
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• v.34 no.3
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• pp.429-438
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• 2012

This study presents two reversible data hiding schemes based on the coefficient shifting (CS) algorithm. The first scheme uses the CS algorithm with a mean predictor in the spatial domain to provide a large payload while minimizing distortion. To guard against manipulations, the second scheme uses a robust version of the CS algorithm with feature embedding implemented in the integer wavelet transform domain. Simulations demonstrate that both the payload and peak signal-to-noise ratio generated by the CS algorithm with a mean predictor are better than those generated by existing techniques. In addition, the marked images generated by the variant of the CS algorithm are robust to various manipulations created by JPEG2000 compression, JPEG compression, noise additions, (edge) sharpening, low-pass filtering, bit truncation, brightness, contrast, (color) quantization, winding, zigzag and poster edge distortion, and inversion.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.189-192
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• 2001

A new configuration of acoustic echo canceler with stepsize predictor and comparator is proposed in this paper. Conventional acoustic echo cancelers using ES(Exponential Step)algorithm has fast convergence speed, but very weak in interference of environment. The proposed stepsize predictor and comparator improve conventional acoustic echo canceler's defects. The Stepsize predictor generates a stepsize value using residual power of error signal. The stepsize comparator selects the stepsize value that is better performance in a acoustic echo canceler using a stepsize decision factor. The Simulation results show superiority of the proposed acoustic echo canceler in environment interference.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.974-986
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• 2016

Reversible image watermarking, a type of digital data hiding, is capable of recovering the original image and extracting the hidden message with precision. A number of reversible algorithms have been proposed to achieve a high embedding capacity and a low distortion. While numerous algorithms for the achievement of a favorable performance regarding a small embedding capacity exist, the main goal of this paper is the achievement of a more favorable performance regarding a larger embedding capacity and a lower distortion. This paper therefore proposes a reversible data hiding algorithm for which a novel piecewise 2D auto-regression (P2AR) predictor that is based on a rhombus-embedding scheme is used. In addition, a minimum description length (MDL) approach is applied to remove the outlier pixels from a training set so that the effect of a multiple linear regression can be maximized. The experiment results demonstrate that the performance of the proposed method is superior to those of previous methods.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.85-95
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• 2009

In the binaural synthesis environments, wide varieties of the head-related transfer functions (HRTFs) that have measured with a various direction would be desirable to obtain the accurate and various spatial sound images. To reduce the size' of HRTFs, interpolation has been often employed, where the HRTF for any direction is obtained by a limited number of the representative HRTFs. In this paper, we study on the distortion measures for interpolation, which has an important role in interpolation. With lhe various objective distortion metrics, the differences between the interpolated and the measured HRTFs were computed. These were then compared and analyzed with the results from the listening tests. From the results, the objective distortion measures were selected, that reflected the perceptual differences in spatial sound image. This measure was employed in a practical interpolation technique. We applied the proposed method to four kinds of an HRTF set, measured from three human heads and one mannequin. As a result, the Mel-frequency cepstral distortion was shown to be a good predictor for the differences in spatial sound location, when three HRTF measured from human, and the time-domain signal to distortion ratio revealed good prediction results for the entire four HRTF sets.

• Journal of Power Electronics
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• v.4 no.2
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• pp.102-111
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• 2004

This paper is concerned with a deadbeat current control implementation of shunt-type three-phase active power filter (APF). Although the one-dimensional deadbeat control method can attain time-optimal response of APF compensating current, one sampling period is actually required fur its settling time. This delay is a serious drawback for this control technique. To cancel such a delay and one more delay caused by DSP execution time, the desired APF compensating current has to be predicted two sampling periods ahead. Therefore an adaptive predictor is adopted for the purpose of both predicting the control error of two sampling periods ahead and bringing the robustness to the deadbeat current control system. By adding the adaptive predictor output as an adjustment term to the reference value of half a source voltage period before, settling time is made short in a transient state. On the other hand, in a steady state, THD (total harmonic distortion) of the utility grid side AC source current can be reduced as much as possible, compared to the case that ideal identification of controlled system could be made.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.79-85
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• 2010

In video standards such as H.264/AVC, motion estimation (ME) / compensation (MC) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. The full search technique, which is used in general video codecs, gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has benn proposed. Among them, NPDS show that can maintain its video quality very close to the full search technique while achieving computation reduction by using a halfway-stop technique in the calculation of block distortion measure. In this paper, we proposed algorithm by determining minimum distortion measure with predictive motion vector and using the new search order. As the result, we can check that the proposed algorithm reduces the computational load 95% in average compared to the full search, respectively with the PSNR lost about 0.04dB.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.90-96
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• 1995

A new method for autoregressive parameter estimation from noisy observation sequence is presented. This method, termed the AP method, is a result of an attempt to make use of the adaptive predictor which is a simple and reliable way of parameter estimation. It is shown theoretically that, for noisy input, the parameter vector computed from the prediction sequence is closer to that of the original sequence than the noisy input sequence is, under the spectral distortion criterion. Simulation results with the Kalman filter as a noise reduction filter and real speech data supported the theory. Roughly speaking, the performance of the parameter set obtained by the AP method is better than noisy one but worse than the EM iteration results. When the simplicity is considered, it could provide a useful alternative to more complicated parameter estimation methods in some applications.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.32-40
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• 2012

Efficient Global Optimization (EGO) method is a global optimization technique which can select the next sample point automatically by infill sampling criteria (ISC) and search for the global minimum with less samples than what the conventional global optimization method needs. ISC function consists of the predictor and mean square error (MSE) provided from the kriging model which is a stochastic metamodel. Also the constrained EGO method can minimize the objective function dealing with the constraints under EGO concept. In this study the constrained EGO method applied to the RAE2822 airfoil shape design formulated with the constraint. But the noisy CFD data caused the kriging model to fail to depict the true function. The distorted kriging model would make the EGO deviate from the correct search. This distortion of kriging model can be handled with the interpolation(p=free) kriging model. With the interpolation(p=free) kriging model, however, the search of EGO solution was stalled in the narrow feasible region without the chance to update the objective and constraint functions. Then the accuracy of EGO solution was not good enough. So the three-step search method was proposed to obtain the accurate global minimum as well as prevent from the distortion of kriging model for the noisy constrained CFD problem.