• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.176-179
• /
• 2010

In this paper, we propose a fast implementation of Bilateral filter for tone mapping algorithm. Bilateral filter is able to preserve detail while at the same time prevent halo-ing artifacts because of improper scale selection by ensuring image smoothed that not only depend on pixel closeness, but also similarity. We accelerate Bilateral filter by using a piecewise linear approximation and recursive Gaussian filter as its domain filter. Recursive Gaussian filter is scale independent filter that combines low cost 1D filter which makes this filter much faster than conventional convolution filter and filtering in frequency domain. The experiment results show that proposed method is simpler and faster than previous method without mortgaging the quality.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.4
• /
• pp.817-823
• /
• 2009

This paper proposes a robust method for mapping of a caterpillar-type mobile robot which inherently has uncertainty in its modeling by compensating for the estimated pose error of the robot. In general, a caterpillar type robot is difficult to model, which results in inaccuracy in Simultaneous Localization And Mapping(SLAM). To enhance the robustness of the SLAM for a caterpillar-type mobile robot, we factorize the SLAM posterior, where we used particle filter to estimate the position of the robot and Extended Kalman Filter(EKF) to map the environment. The simulation results show the effectiveness and robustness of the proposed method for mapping.

• Journal of Broadcast Engineering
• /
• v.23 no.2
• /
• pp.283-292
• /
• 2018

Devices capable of capturing and displaying high dynamic range (HDR) images with significantly increased brightness range compared to low dynamic range (LDR) images have been developed and various methods for efficiently converting the brightness range of an image have been developed. In this paper, we propose a reverse tone mapping method using a guided filter to efficiently convert LDR images into HDR images. After obtaining brightness enhancement function (BEF) using a guided filter, we can reconstruct HDR image from one LDR image. In addition, when the image is too bright or dark, the proposed method maximizes the image quality of the reconstructed HDR image by estimating and adjusting the exposure value before expanding the brightness range of images. Computer simulations show that the proposed method produces HDR images of superior quality compared with the conventional methods.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2003.06a
• /
• pp.268-271
• /
• 2003

There are several methods for the design of 2D filter. Notable among them is McClellan transform method. This transform allows us to obtain a high order 2D FIR filter through mapping the 1D frequency points of a 1D prototype FIR filter onto 2D frequency contours. We design 2D filter using this transform. Then we notice for mapping deviation of the 2D filter. In this paper, Quadratic programming (QP) method allows us to obtain coefficients of McClellan transform. Then we compare deviation of QP method with least-squares(LS) method. Elliptic filter is used for comparison. The optimal cutoff frequencies of a 1D filter are obtained directly from the QP method. Also several problem of LS method are solved.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.3
• /
• pp.251-268
• /
• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.4
• /
• pp.553-563
• /
• 1994

This paper presents a filtering method using neural networks to extract fundamental frequency components of the transient wave signals in power systems. Based on the ability of multilayer feedforward neural networks to approximate any continuous function, a neural networks mapping filter is proposed for the protective distance relaying systems to extract the effective components efficiently. A characteristic feature of this mapping filter is composed of the multilayer perceptron neural networks which are trained by using random signals and those are mapped to the DFT filtering computational structure by GDR(Generalized Delta Rule). The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.1
• /
• pp.55-60
• /
• 2011

The most basic algorithm in SLAM(Simultaneous Localization And Mapping) technique of mobile robots is EKF(Extended Kalman Filter) SLAM. However, it requires prior information of characteristics of the system and the noise model which cannot be estimated in accurate. By this limit, Kalman Filter shows the following behaviors in a highly uncertain environment: becomes too sensitive to internal parameters, mathematical consistency is not kept, or yields a wrong estimation result. In contrast, $H_{\infty}$ filter does not requires a prior information in detail. Thus, based on a idea that $H_{\infty}$ filter based SLAM will be more robust than the EKF-SLAM, we propose a framework of $H_{\infty}$ filter based SLAM and show that suggested algorithm shows slightly better result man me EKF-SLAM in a highly uncertain environment.

• Journal of Korea Multimedia Society
• /
• v.22 no.1
• /
• pp.10-17
• /
• 2019

In High Dynamic Range (HDR) image processing, tone mapping is the process to compress an input image into a Low Dynamic Range (LDR) image. In most cases, the reason that detail preservation is prior to take over tone mapping is that the dynamic range is significantly different between input and output images. In the case of iCAM06, details are separated by using a bilateral filter, however, it causes noise amplification at the dim surround region. Thus, we suggest that the detail signal, which is separated from the bilateral filter, is combined with the base signal after an adaptive Kalman filter is applied according to the local standard deviation. We confirmed that the proposed method enhances the HDR images quality by checking the noise reduction in a dim surround region.

• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.217-226
• /
• 2019

In this paper, we propose a filtering method that can improve the results of inverse tone-mapping using guided image filter. Inverse tone-mapping techniques have been proposed that convert LDR images to HDR. Recently, many algorithms have been studied to convert single LDR images into HDR images using CNN. Among them, there exists an algorithm for restoring pixel information using CNN which learned to restore saturated region. The algorithm does not suppress the noise in the non-saturation region and cannot restore the detail in the saturated region. The proposed algorithm suppresses the noise in the non-saturated region and restores the detail of the saturated region using a WGIF in the input image, and then applies it to the CNN to improve the quality of the final image. The proposed algorithm shows a higher quantitative image quality index than the existing algorithms when the HDR quantitative image quality index was measured.

• Journal of the Optical Society of Korea
• /
• v.18 no.5
• /
• pp.449-452
• /
• 2014

We present a multi-tap microwave photonic filter with high selectivity through applying time-to-frequency mapping and optical frequency comb shaping techniques. When arranged in the time-to-frequency mapping stage, by a Fourier transform, the deviation of the optical taps to the target profile is significantly reduced while maintaining the apodization profile, resulting in high sidelobe suppression in the filters. By applying a simple time-to-frequency mapping stage to the conventional optical frequency combs, we demonstrate a substantially enhanced (>10dB) sidelobe suppression, resulting in filter lineshapes exhibiting a significantly high (>40dB) main lobe to sidelobe suppression ratio. These results highlight the potential of the technique for implementation in various passband filters with high sidelobe suppression.