• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.736-739
• /
• 2006

While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.36T no.4
• /
• pp.24-29
• /
• 1999

In this paper, a simple contour-preserving filtering algorithm is proposed. The goal of the contour-preserving filtering method is to remove noise ad granularity as the preprocessing for the image segmentation procedure. Our method finds edge map and separates the image into the edge region and the non-edge region using this edge map. For the non-edge region, typical smoothing filters could be used to remove the noise and the small areas during the segmentation procedure. The result of simulation shows that our method is slightly better than the typical methods such as the median filtering and gradient inverse weighted filtering in the point of view of analysis of variance (ANOVA).

• Journal of Information Processing Systems
• /
• v.7 no.1
• /
• pp.103-110
• /
• 2011

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

• Journal of applied mathematics & informatics
• /
• v.8 no.3
• /
• pp.731-742
• /
• 2001

A Gaussian smoothing algorithm obtained from a cascade of convolutions with a seven-point kernel is described. We prove that the change of local sums after applying our algorithm to sinusoidal signals is reduced to about two thirds of the change by the binomial coefficients. Hence, our seven point kernel is better than the binomial coefficients when trend curves are needed to be generated. We also prove that if our Gaussian convolution is applied to sinusoidal functions, the amplitude of higher frequencies reduces faster than the lower frequencies and hence that it is a low pass filter.

• Journal of IKEEE
• /
• v.19 no.2
• /
• pp.244-253
• /
• 2015

Please This paper presents method of video stabilization based on detection and adaptive motion smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8B
• /
• pp.822-829
• /
• 2009

A reader protocol is an interface between a host and RFID readers. There are several standards for reader protocol such as EPCglobal Low Level Reader Protocol (LLRP) 1.0.1, EPCglobal Reader Protocol (RP) 1.1, and ISO/IEC 15961/15962. Unfortunately, these standards focus on the passive RFID system, and so they are not appropriate for the active RFID system. In this paper, we implemented an efficient reader protocol for the active RFID system, which is based on EPCglobal LLRP 1.0.1, but smoothing/filtering functions of EPCglobal RP 1.1 are added. This protocol is designed to configure air interface parameters for active RFID readers and tags. It can reduce the amount of data transfer between the reader and host by filtering function, and can improve the performance of tag collection by smoothing function. In addition, it can remove inefficiency caused by tag memory data change according to the standards of ISO/IEC 15961/15962. In the real-world environment, we evaluated the performance of our implemented reader protocol using one RFID reader and 45 tags.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.2
• /
• pp.691-702
• /
• 2013

In this study the quantitative outlier-filtering algorithm has been developed using the smoothing method based on the day-of-the-week traffic volume variation pattern and then, in order to test the effectiveness of the algorithm, it has been used to identify outliers from the traffic volume data collected at 14 continuous traffic counts sites on the national highways in the year 2010. The test results are satisfactory since the filtering rate is 98.2% for normal days and the mis-filtering rate is 8.0% for abnormal days. Therefore, the algorithm will be able to be used for roughly-but-quickly filtering outliers from the collected traffic volume data.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.12
• /
• pp.1015-1023
• /
• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• Proceedings of the KSR Conference
• /
• 2003.10c
• /
• pp.247-251
• /
• 2003

The velocity of train which is measured from pulse generator attached to TM is used for displaying or control signal of inverter and so on. Measured signals increase and decrease step-by-step by pulse counting or monotonously by F/V conversion. But noises and signal distortions by measuring error like alias make it difficult to provide correct velocity infomation and estimate the acceleration. In this paper, we investigated the performance of Smoothing method for suppressing the noises in velocity signals. And the difference between Smoothed signal and origin velocity signals is inspected and the comparison with low pass filtering show applicable of Smoothing method for noise rejection and the estimation of signal. Finally, acceleration curves estimated from Smoothing method are compared with real accelerator signal attached to train.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.345-346
• /
• 2009

The segmentation of vessel including portal vein, hepatic vein and artery, from Computed Tomography (CT) images plays an important role in the therapeutic strategies for hepatic diseases. Representing segmented vessels in three dimensional spaces is extremely useful for doctors to plan liver surgery. In this paper, proposed method is focused on smoothing technique of segmented 3D liver vessels, which derived from 3D region growing approach. A pixel expand algorithm has been developed first to avoid vessel lose and disconnection cased by the next smoothing technique. And then a binary volume filtering technique has been implemented and applied to make the segmented binary vessel volume qualitatively smoother. This strategy uses an iterative relaxation process to extract isosurfaces from binary volumes while retaining anatomical structure and important features in the volume. Hard and irregular place in volume image has been eliminated as shown in the result part, which also demonstrated that proposed method is a suitable smoothing solution for post processing of fine vessel segmentation.