• ETRI Journal
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• v.8 no.1
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• pp.3-5
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• 1986

본 고는 image의 pattern을 identify하기 위해 그 image data의 FFT(Fast Fourier Transform)를 취한 후 에너지 스펙트럼의 크기를 폐적분한 값으로 부터 original input object와 비교대상의 object에 대한 mean square error 값의 차이를 시뮬레이션한 결과 얻은 threshold value와 비교함으로써 matching 을 구현하기 위함이다. Vax11-780/vms와 Fortran77 Language를 사용하여 시뮬레이션을 수행하였으며 Tektronix graphic terminal이 digitized된 이미지의 모니터용으로 사용되었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1897-1904
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• 1996

This study intends to extract the efficient spectrum characteristics of the fingerpriint image in the fourier domain and to apply them for image enhancement. In order to effectively acquire the spectrum characteristics of the fingerprint in the fourier domain, I set up a 1*64 window as a processing unit and, combining various kinds of the record and overlap lengths, made the power spectrum density estimate for each of those combinations. each spectrum characeristic acquired was applied to a re-synthesis process of the fingerprint image, and, through comparisons and evaluations of the resultant images, an improved gray scale image could be obtained. The validity of this algorithm could be confirmed by the comparison and evaluation fo the binary images which were grained on the established method and the one I used in this experiment.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.754-764
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• 2016

The exhaustive list of sparsification methods for a digital image suffers from achieving an adequate number of zero and near-zero coefficients. The method proposed in this paper, which is known as the Discrete Rajan Transform Sparsification, overcomes this inadequacy. An attempt has been made to compare the simulation results for benchmark images by various popular, existing techniques and analyzing from different aspects. With the help of Discrete Rajan Transform algorithm, both lossless and lossy sparse representations are obtained. We divided an image into $8{\times}8-sized$ blocks and applied the Discrete Rajan Transform algorithm to it to get a more sparsified spectrum. The image was reconstructed from the transformed output of the Discrete Rajan Transform algorithm with an acceptable peak signal-to-noise ratio. The performance of the Discrete Rajan Transform in providing sparsity was compared with the results provided by the Discrete Fourier Transform, Discrete Cosine Transform, and the Discrete Wavelet Transform by means of the Degree of Sparsity. The simulation results proved that the Discrete Rajan Transform provides better sparsification when compared to other methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.1001-1007
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• 2014

This paper proposes a method to reduce operation time using discrete cosine transform and to improve image quality by the DC gain correction. Conventional filtered back projection (FBP) filtering in the frequency domain using Fourier transform, but the filtering process uses complex number operations. To simplify the filtering process, we propose a filtering process using discrete cosine transform. In addition, the image quality of reconstructed images are improved by correcting DC gain of sinograms. To correct the DC gain, we propose to find an optimum DC weight is defined as the ratio of sinogram DC and optimum DC. Experimental results show that the proposed method gets better performance than the conventional method for phantom and clinical CT images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.570-595
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• 2017

Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1041-1042
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• 2008

The wavelet transform has an advantage over the Fourier transform for representing in homogeneous functions that have discontinuities, sharp peaks, ike images. This paper proposes a noise variance estimation method by utilizing the wavelet transform.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.7
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• pp.499-506
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• 2003

In this paper, we propose the shift and noise tolerance method using a virtual phase image and a joint transform correlator (JTC) architecture that can alleviate the need for an accurate optical axis alignment. An encrypted image is obtained by the Fourier transform of the product of a phase- encoded virtual image to camouflage the original one and a random phase image. Therefore, even if unauthorized users analyze the encrypted image, we can prevent the possibility of counterfeiting from unauthorized people using virtual image which dose not contain any information from the original image. We demonstrate the robustness to noise, to data loss and to shift of the encrypted image using a JTC in the proposed description technique.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.2
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• pp.195-206
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• 2022

The separation of spectrally overlapped broadband echo signals from free-swimming Japanese needlefish Hypohamphus sajori using the fractional Fourier transform (FrFT) was investigated. The broadband echo signals were measured over frequency ranges of 40-80 and 110-220 kHz. The overlapped echo signals were separated after eliminating noise signals in the smoothed pseudo-Wigner-Ville distribution domain. The echo signal from a 40 mm WC sphere suspended just below a chirp transducer was used to calibrate the broadband of the chirp echo sounder and estimate the frequency dependence of target strength for the separated echo signals. The experimental results show that the proposed FrFT method can analyze the time-frequency image of broadband echo signals from free-swimming individual fish effectively and can be used as a quantitative tool for extracting the acoustic features used for fish species identification.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.933-942
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• 2021

The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in the surface image velocimetry. Among them the spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity for a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analyzing time so much. It, however, has a little drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it may cause singnificant error in velocity. The present study aims to propose a new method to find out the main flow direction by using a fast Fourier transform(FFT) to a spatio-temporal (image) volume, which were constructed by accumulating the river surface images along the time direction. The method consists of two steps; the first step for finding main flow direction in space image and the second step for calculating the velocity magnitude in main flow direction in spatio-temporal image. In the first step a time-accumulated image was made from the spatio-temporal volume along the time direction. We analyzed this time-accumulated image by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image in main flow direction was extracted from the spatio-temporal volume. Once again, the spatio-temporal image was analyzed by FFT and velocity magnitudes were calculated from the transformed image. The proposed method was applied to a series of artificial images for error analysis. It was shown that the proposed method could analyze two-dimensional flow field with fairly good accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.7
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• pp.656-665
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• 2015

In this paper, we improved the clarity and quality of the radar imaging by applying motion compensation for time-frequency transform in B-ISAR imaging. The proposed motion compensation algorithm using UWB radar is verified. B-ISAR algorithm procedure and time-frequency transform for improved motion compensation are provided for theoretical ground. The image was created by a UWB Radar B-ISAR imaging algorithm method. Also, creating a B-ISAR imaging algorithm for motion compensation of time-frequency transformation method was used. The B-ISAR Imaging algorithm is implemented using STFT(Short-Time Fourier Transform), GWT(Gabor Wavelet Transform), and WVD(Wigner-Ville Distribution) approaches. The performance of STFT is compared with the GWT and WVD algorithms. It is found that the WVD image shows more clarity and decreased spread phenomenon than other methods.