• Journal of Broadcast Engineering
• /
• v.23 no.1
• /
• pp.138-145
• /
• 2018

In this paper, we propose a new motion estimation algorithm for frame rate up-conversion. The proposed algorithm uses the variance of errors in addition to SAD in motion estimation to find more accurate motion vectors. Then, it decides which motion vectors are wrong using the variance of neighbor motion vectors and the variance between current motion vector and neighbor's average motion vector. Next, incorrect motion vectors are corrected by weighted sum of eight neighbor motion vectors. Additionally, we propose adaptive search range algorithm, so we can find more accurate motion vectors and reduce computational complexity at the same time. As a result, proposed algorithm improves the average peak signal-to-noise ratio and structural similarity up to 1.44 dB and 0.129, respectively, compared with previous algorithms.

• Journal of Communications and Networks
• /
• v.14 no.5
• /
• pp.540-545
• /
• 2012

In this paper, the lagged cross-correlation of two probability density functions constructed by kernel density estimation is proposed, and by maximizing the proposed function, adaptive filtering algorithms for supervised and unsupervised training are also introduced. From the results of simulation for blind equalization applications in multipath channels with impulsive and slowly varying direct current (DC) bias noise, it is observed that Gaussian kernel of the proposed algorithm cuts out the large errors due to impulsive noise, and the output affected by the DC bias noise can be effectively controlled by the lag ${\tau}$ intrinsically embedded in the proposed function.

• Journal of Korea Multimedia Society
• /
• v.6 no.7
• /
• pp.1149-1158
• /
• 2003

Content adaptive watermark embedding algorithm using a stochastic image model in the multiwavelet transform is proposed in this paper. A watermark is embedded into the perceptually significant coefficients (PSCs) of each subband using multiwavelet transform. The PSCs in high frequency subband are selected by SSQ, that is, by setting the thresholds as the one half of the largest coefficient in each subband. The perceptual model is applied with a stochastic approach based on noise visibility function (NVF) that has local image properties for watermark embedding. This model uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The watermark estimation use shape parameter and variance of subband region. it is derive content adaptive criteria according to edge and texture, and flat region. The experiment results of the proposed watermark embedding method based on multiwavelet transform techniques were found to be excellent invisibility and robustness.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.5C
• /
• pp.556-564
• /
• 2007

This paper proposes an efficient scheme to track a time variant channel induced by multi-path Rayleigh fading in mobile MIMO-OFDM systems with null sub-carriers. The proposed adaptive channel tracking scheme removes in the frequency domain the interfering signals of the other transmit (Tx) antennas by using a predicted channel frequency response before starting the channel estimation. Time domain channel estimation is then performed to reduce the additive white Gaussian noise (AWGN). The simulation results show that the proposed method is better than the conventional channel tracking method [3] in time varying channel environments. At a Doppler frequency of 300 Hz and bit error rates (BER) of 10-3, signal-to-noise power ratio (Eb/N0) gains of about 2.5 dB are achieved relative to the conventional channel tracking method [3]. At a Doppler frequency of 600 Hz, the performance difference between the proposed method and conventional one becomes much larger.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.12
• /
• pp.2783-2797
• /
• 1997

This paper proposes a new motion estimation algorithm that employs matching in a variable search area. Instead of uisg a fixed search range for coarse motion estimation, we examine a varying search range, which is determined adaptively by the peak signal to noise ratio (PSNR) of the frame difference. The hexagonal matching method is one of the refined methods in image warping. It produces improved image quality, but it requires a large amount of computataions. The proposed adaptive partial matching method reduces computational complexity below about 50% of the hexagonal matching method, while maintaining the image quality comparable. The performance of two motion compensation methods, which combine the affine or bilinear transformation with the proposed motion estimation algorithm, is evaluated based on the following criteria:computtational complexity, number of coding bits, and reconstructed image quality. The quality of reconstructed images by the proposed method is substantially improved relative to the conventional BMA method, and is comparable to the full hexagonal matching method;in addition, computational complexity and the number of coding bits are reduced significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1603-1623
• /
• 2020

Multiple Mobile Robots System (MMRS) has shown many attractive features in lots of real-world applications that motivate their rapid and wide diffusion. In MMRS, the Cooperative Localization (CL) is the basis and premise of its high-performance task. However, the statistical characteristics of the system noise should be already known in traditional CL algorithms, which is difficult to satisfy in actual MMRS because of the numerous of disturbances form the complex external environment. So the CL accuracy will be reduced. To solve this problem, an improved Adaptive Active Cooperative Localization (A²CL) algorithm based on information optimization strategy for MMRS is proposed in this manuscript. In this manuscript, an adaptive information fusion algorithm based on the variance component estimation under Extended Kalman filter (VCEKF) method for MMRS is introduced firstly to enhance the robustness and accuracy of information fusion by estimating the covariance matrix of the system noise or observation noise in real time. Besides, to decrease the effect of observation uncertainty on CL accuracy further, an observation optimization strategy based on information theory, the Model Predictive Control (MPC) strategy, is used here to maximize the information amount from observations. And semi-physical simulation experiments were carried out to verity the A²CL algorithm's performance finally. Results proved that the presented A²CL algorithm based on information optimization strategy for MMRS cannot only enhance the CL accuracy effectively but also have good robustness.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.14 no.3
• /
• pp.513-525
• /
• 1990

This paper presents Adaptive Robust Servocontrol(ARSC) scheme, which is an explicit(or indirect) pole-assignment adaptive algorithm with the property of "robustness". It guarantees asymptotic regulation and tracking in the presence of finite parameter perturbations of the unknown plant(or process) model. The controller structure is obtained by transforming a robust control theory into an adaptive control version. This controller structure is combined with the model estimation algorithm which includes a dead-zone for bounded noise. It is proved theoretically that this combination of control and identification is globally convergent and stable. It is also shown, through a real-time simulation study, that the desired closed-loop poles of the augmented system can be assigned directly, and that the adjustment mechanism of the scheme tunes the controller parameters according to the assigned closed-loop poles.oop poles.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.12
• /
• pp.2511-2520
• /
• 2011

This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.

• Journal of Broadcast Engineering
• /
• v.13 no.6
• /
• pp.915-929
• /
• 2008

In this paper, we propose an algorithm for pixel-based disparity estimation with reliability in the multi-view image. The proposed method estimates an initial disparity map using edge information of an image, and the initial disparity map is used for reducing the search range to estimate the disparity efficiently. Furthermore, disparity-mismatch on object boundaries and textureless-regions get reduced by adaptive block size. We generated intermediate-view images to evaluate the estimated disparity. Test results show that the proposed algorithm obtained $0.1{\sim}1.2dB$ enhanced PSNR(peak signal to noise ratio) compared to conventional block-based and pixel-based disparity estimation methods.

• Journal of the Institute of Convergence Signal Processing
• /
• v.11 no.4
• /
• pp.270-277
• /
• 2010

The BAMS filter is a kind of wavelet shrinkage filter based on the Bayes estimators with no simulation, therefore it can be used for a real time filter. The denoising efficiency of BAMS filter is seriously affected by the estimated noise variance in each wavelet band. To remove noise in signals in existing BAMS filter, the noise variance is estimated by using the quartile of the finest level of details in the wavelet decomposition, and with this variance, the noise of the level is removed. In this paper, to remove the image noise includingodified quartile of the level of detail is proposed. And by these techniques, the image noises of mid and high frequency bands are removed, and the results showed that the increased PSNR of ab the midband noise, the noise variance estimation method using the monotonic transform and the mout 2[dB] and the effectiveness in denosing of low noise deviation images.