• Title/Summary/Keyword: Wavelet Band

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Accuracy Assessment of Sharpening Algorithms of Thermal Infrared Image Based on UAV (UAV 기반 TIR 영상의 융합 기법 정확도 평가)

  • Park, Sang Wook;Choi, Seok Keun;Choi, Jae Wan;Lee, Seung Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.6
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    • pp.555-563
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    • 2018
  • Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

The Feature Extraction of Partial Discharge Electromagnetic Wave utilizing Signal Processing Techniques (신호처리 기술에 의한 부분방전 방사전자파의 특징 추출)

  • 이현동;이광식
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.16 no.1
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    • pp.44-49
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    • 2002
  • In recent years, diagnostic techniques have been investigated to detect a partial discharge(PD) in a high voltage electrical equipment. Because PD signal is very sensitive and difficult to suppress strong noises such as narrow-band radio frequency noise and random noise, the accuracy and credibility of PD measurement might be influenced by surrounding interference. Using the technique of PD detection by electromagnetic wave, we have studied the characteristics of both PD and substation-in interference signal. Also, we propose a wavelet packet transform based technique to perform a feature extraction from the interference and PD signal and a classification of the extracted features. The results show that time-frequency characteristics between PD and interference can be obviously distinguished. It is helpful for the development of the insulation diagnosis technique.

Defect Detection of Flat Panel Display Using Wavelet Transform (웨이블릿 변환을 이용한 FPD 결함 검출)

  • Kim, Sang-Ji;Lee, Youn-Ju;Yoon, Jeong-Ho;You, Hun;Lee, Byung-Gook;Lee, Joon-Jae
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.10 no.1
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    • pp.47-60
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    • 2006
  • Due to the uneven illumination of FPD panel surface, it is difficult to detect the defects. The paper proposes a method to find the uneven illumination compensation using wavelets, which are done based on multi-resolution structure. The first step is to decompose the image into multi-resolution levels. Second, elimination of lowest smooth sub-image with highest frequency band removes the high frequency noise and low varying illumination. In particular, the main algorithm was implemented by lifting scheme for realtime inline process.

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A Robust Pattern Digital Watermarking Method using Wavelet Transform (웨이브릿 기반의 강인한 패턴 디지털 워터마킹 방법)

  • 이경훈;김용훈;이태홍
    • Journal of Korea Multimedia Society
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    • v.7 no.1
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    • pp.98-105
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    • 2004
  • In this paper, we proposed a watermarking algorithm for embedding visually recognizable pattern into the middle-frequency part:; of image. Binary image as watermark is embedded in the LH2, HL2 and HH2 band of wavelet transformed domain for copyright protection of image data. To evaluate robustness of the proposed method, we applied some basic algorithm of image processing such as scaling, filtering, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method has the good image quality and the high perceptibility of watermark. It was demonstrated by experiments that the proposed algorithm can provide an excellent protection under various attacks.

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A Study on the Characteristics of Partial Discharge Signal by Multiresolution Decomposition (다중해상도 분해에 의한 부분방전 신호의 특징에 관한 연구)

  • Lee, Hyui1-Dong;Kim, Chung-Nyun;Lee, Kwang-Sik;Lee, Dong-In;Choi, Sang-Tae;Lee, Done-Heon
    • Proceedings of the KIEE Conference
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    • 2000.07c
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    • pp.1924-1926
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    • 2000
  • This paper deals with the multiresolution analysis of wavelet transform for partial discharge(PD).PD is an electrical discharge that only partically bridges the insulation performance of electrical equipment in high voltage. PD signal is very sensitive and difficult to suppress strong noises such as narrow-band radio frequency noise and random noise. In recently, wavelet transform has become a powerful tool to analysis and process signals in various science and technology fields. In this paper, daubechies family is adopted for the research of the characteristics of PD signals. The results show that the kurtosis is increased with discharge process and skewness is decreased with discharge process, but when PD occured positive range then skewness is increased. Segment 7, 8, 9, 10, 11 values is increased with discharge process, so phase distribution is characterized by 210$\sim$330 ranges.

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Optimal EEG Feature Extraction using DWT for Classification of Imagination of Hands Movement

  • Chum, Pharino;Park, Seung-Min;Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.786-791
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    • 2011
  • An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.

PVC Classification Algorithm Through Efficient R Wave Detection

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of Sensor Science and Technology
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    • v.22 no.5
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    • pp.338-345
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    • 2013
  • Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

Spatial Focalization of Zen-Meditation Brain Based on EEG

  • Liu, Chuan-Yi;Lo, Pei-Chen
    • Journal of Biomedical Engineering Research
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    • v.29 no.1
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    • pp.17-24
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    • 2008
  • The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.

Optimization of Pipelined Discrete Wavelet Packet Transform Based on an Efficient Transpose Form and an Advanced Functional Sharing Technique

  • Nguyen, Hung-Ngoc;Kim, Cheol-Hong;Kim, Jong-Myon
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.374-385
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    • 2019
  • This paper presents an optimal implementation of a Daubechies-based pipelined discrete wavelet packet transform (DWPT) processor using finite impulse response (FIR) filter banks. The feed-forward pipelined (FFP) architecture is exploited for implementation of the DWPT on the field-programmable gate array (FPGA). The proposed DWPT is based on an efficient transpose form structure, thereby reducing its computational complexity by half of the system. Moreover, the efficiency of the design is further improved by using a canonical-signed digit-based binary expression (CSDBE) and advanced functional sharing (AFS) methods. In this work, the AFS technique is proposed to optimize the convolution of FIR filter banks for DWPT decomposition, which reduces the hardware resource utilization by not requiring any embedded digital signal processing (DSP) blocks. The proposed AFS and CSDBE-based DWPT system is embedded on the Virtex-7 FPGA board for testing. The proposed design is implemented as an intellectual property (IP) logic core that can easily be integrated into DSP systems for sub-band analysis. The achieved results conclude that the proposed method is very efficient in improving hardware resource utilization while maintaining accuracy of the result of DWPT.

Quantitative Nondestructive Evaluation in Composite Beam Using Piezoelectric Transducers (압전 변환기를 이용한 복합재료 보의 비파괴 평가)

  • Lee, Sang-Hyoup;Choi, Young-Geun;Kim, Sang-Tae
    • Composites Research
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    • v.20 no.3
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    • pp.31-36
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    • 2007
  • A quantitative prediction method for initial crack length in a carbon/epoxy (CF/EP) composite beam using active piezoelectric transducers was established in this study. Wavelet Transform (WT)-based signal processing and identification technique in time-frequency domain was developed to facilitate the determination of damage presence and severity. Dynamic response of a CF/EP composites beam containing a continuously expanding crack, coupled with a pair of active piezoelectric disks, was examined under a narrow band excitation, and then applied with the proposed signal processing technique.