• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.18-24
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• 2010

A correct and accurate model of optical data storage systems is very important in development and performance evaluation of various data detection algorithms. In this paper, we present an nonlinear modeling scheme of a super-resolution near-field structure (Super-RENS) read-out signal using the canonical piecewise-linear (PWL) and the second-order Volterra models. Nonlinear equalizers may be developed on the basis of the information obtained from this nonlinear modeling. To mitigate the nonlinear inter-symbol interference (ISI), we proposed a new nonlinear equalizer for Super-RENS discs. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The experiment results verified the possibility that the canonical PWL and the second-older Volterra models can be utilized for nonlinear modeling of Super-RENS systems. The proposed equalizers are superior to the one without equalization in terms of bit error rate (BER).

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.223-232
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• 2023

A widely used method for monitoring land cover using high-resolution satellite images is to classify the images based on the colors of the objects of interest. In urban areas, not only major objects such as buildings and roads but also vegetation such as trees frequently appear in high-resolution satellite images. However, the colors of vegetation objects often resemble those of other objects such as buildings, roads, and shadows, making it difficult to accurately classify objects based solely on color information. In this study, we propose a method that can accurately classify not only objects with various colors such as buildings but also vegetation objects. The proposed method uses the normalized difference vegetation index (NDVI) image, which is useful for detecting vegetation objects, along with the RGB image and classifies objects into subclasses. The subclass classification results are fused, and the final classification result is generated by combining them with the image segmentation results. In experiments using Compact Advanced Satellite 500-1 imagery, the proposed method, which applies the NDVI and subclass classification together, showed an overall accuracy of 87.42%, while the overall accuracy of the subchannel classification technique without using the NDVI and the subclass classification technique alone were 73.18% and 81.79%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3A
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• pp.342-350
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• 2000

In this paper, the bit error performance for the reverse link of a synchronous direct sequence code division multiple access (DS-CDMA) system employing an imperfect power control scheme over a frequency selective Rayleigh fading channel is analyzed. The system capacity degradation due to power control error (PCE), which is approximated by a log-normally distributed random variable, is estimate as a function of a standard deviation of the PCE. In addition, the impact of the multipath intensity profile (MIP) shape and the number of resolvable paths on the performance of the synchronous transmission is investigated. To estimate the system capacity, the coded bit error performance is evaluated and compared with the conventional CDMA. It is found tat synchronous transmission has less sensitivity to imperfect power control and eases the power control requirements. In particular, as the decay constant $\delta$ of MIP increases, the synchronous transmission in the DS-CDMA reverse link results in a significant BER improvement over the asynchronous transmission even in the presence of imperfect power control. We further conclude that the capacity can be improved by employing the synchronous transmission.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.865-872
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• 2020

In the fifth generation (5G) mobile networks, non-orthogonal multiple access (: NOMA) has been considered as a promising technology, to increase the channel capacity. In NOMA, the multiple users share the channel resources and multiplex simultaneously. Recently, for the stronger channel user, it was reported that the bit-error rate (: BER) performance with interactive mobile users is degraded, compared to the BER of non-interactive users. In this paper, in order to improve such degraded BER performance, we propose the maximum-likelihood (: ML) receiver. First, the closed-form expression for the BER of the ML receiver is derived, and then it is shown that the BER of the ML receiver is improved, compared with the BER of the ideal perfect successive interference cancellation (: SIC) receiver. Additionally, based on the analytical expression, Monte Carlo simulations validates the above-mentioned results.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.58-65
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• 2016

This paper presents optimization techniques to reduce the processing time of the dehazing method and proposes an efficient dehazing method based on them. In the proposed techniques, the atmospheric light is estimated based on the distributed sorting of the dark channel pixels, so as to reduce the computations. The normalization process required in the transmission estimation is simplified by the assumption that the atmospheric light is monochromatic. In addition, the dark channel is modified into the median dark channel in order to eliminate the transmission refinement process while achieving a comparable dehazing quality. The proposed dehazing method based on the optimization techniques is presented and its performance is investigated by developing a prototype system. When compared to the previous method, the proposed dehazing method reduces the processing time by 65% while maintaining the dehazing quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.67-72
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• 2012

In this paper, we present an image enhancement method for atmospherically degraded images using atmospheric light and transmission based on color analysis. We first generate a normalized image using maximum value of each RGB color channel. Then, each atmospheric light is estimated from RGB color channel respectively by calculating reflectance of an image. We also, generate a transmission using gamma coefficients from the Y channel of the image. We can significantly enhance the visibility of an image by using the estimated atmospheric light and the transmission. The proposed algorithm can remove atmospheric degradation components better than existing techniques because the color prevents color distortion which is common problem of existing techniques. Experimental results demonstrate that the proposed algorithm can improve visibility be removing fog, smoke, and dust.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.942-948
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• 2003

In this paper, we analyze the performance of multiple trellis coded modulation applied to continuous phase frequency shift keying (MTCM/CPFSK) for the noncoherent receiver without channel state information (CSI) on the interleaved Rician fading channel. In this system, the squared cross-correlation between the received signal and a candidate signal is used as the branch metric of the Viterbi decoder. To obtain the bit error performance of this system, we analyze the approximated pairwise error probability (PEP) and the exact PEP. We also derive the equivalent normalized squared distance (ENSD) and compare it with the ENSD of the noncoherent receiver with perfect CSI. Simulation results are also provided to verify the theoretical performance analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1003-1010
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• 2020

This paper investigates the achievable data rate for the single-user decoding(SUD) receiver, which does not perform successive interference cancellation(SIC), in contrast to the conventional SIC non-orthogonal multiple access(NOMA) scheme. First, the closed-form expression for the achievable data rate of SUD NOMA with correlated information sources(CIS) is derived, for the stronger channel user. Then it is shown that for the stronger channel user, the achievable data rate of SUD NOMA with independent information sources(IIS) is generally inferior to that of conventional SIC NOMA with IIS. However, for especially highly CIS, we show that the achievable data rate of SUD NOMA is greatly superior to that of conventional SIC NOMA. In addition, to verify the impact of CIS on the achievable data rate of SUD, the extensive comparisons of the achievable data rates for the SUD receiver and the SIC receiver are compared for various correlation coefficients.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.27-34
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• 2005

Iterative detection (ID) has proven to be a near-optimal solution for concatenated Finite State Machines (FSMs) with interleavers over an additive white Gaussian noise (AWGN) channel. When perfect channel state information (CSI) is not available at the receiver, an adaptive ID (AID) scheme is required to deal with the unknown, and possibly time-varying parameters. The basic building block for ID or AID is the soft-input soft-output (SISO) or adaptive SISO (A-SISO) module. In this paper, Reduced State SISO (RS-SISO) algorithms have been applied for complexity reduction of the A-SISO module. We show that serially concatenated CPM (SCCPM) with AID has turbo-like performance over fading ISI channels and also RS-A-SISO systems have large iteration gains. Various design options for RS-A-SISO algorithms are evaluated. Recently developed density evolution technique is used to analyze RS-A-SISO algorithms. We show that density evolution technique that is usually used for AWGN systems is also a good analysis tool for RS-A-SISO systems over frequency-selective fading channels.