• ETRI Journal
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• v.44 no.1
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• pp.125-134
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• 2022

Visible light communication (VLC) systems incorporate ambient lighting and wireless data transmission, and the experienced channel in indoor VLC is a major topic that should be examined for reliable communication. In this study, it is realized that multiple transmitters in classical alignment are the forceful factors for channel characteristics. In the frequency band, fluctuations with sudden drops are observed, where the fluctuation shape is related to the source layout and receiver location. These varying frequency-selective channels need solutions, especially for mobile users, because sustained channel estimation and equalization are necessary as the receiver changes its location. It is proven that using light-emitting diodes (LEDs) with highly directional beams as sources or using a detector with a narrow field of view (FOV) in the receiver may help partially alleviate the problem; the frequency selectivity of the channel reduces in some regions of the room. For flat fading channel characteristics all over the room, LEDs should be aligned in hexagonal cellular structure, and detector FOV should be arranged according to the cell dimension outcomes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.1-8
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• 2013

High-density discrete wavelet transformation is one way to overcome the disadvantages of the standard wavelet transform of shift invariant because it increases the number of subband signals. In this paper, high-density discrete wavelet transform consisting of three channels is applied in a two-dimensional image processing. Experimental results show that the proposed method is well satisfied with the shift invariant and is excellent directional selectivity because it could generate many subband images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.77-83
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• 2014

Over-sampled discrete wavelet transformation is one way to overcome the disadvantages of the standard wavelet transform of shift invariance even though it increases the number of subband signals. Non-separable based discrete wavelet transform is efficient that it satisfies shift invariance and directional selectivity. In this paper, since efficient over-sampled wavelet transform is possible in a two-dimensional image processing, we show that the proposed method is well applied with performance improvement of digital image and noise removal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.52-61
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• 2006

Orthogonal wavelet tansform which is generally used in image and signal processing applications has limited performance because of lack of shift invariance and low directional selectivity. To overcome these demerits complex wavelet transform has been proposed. In this paper, we present an efficient image denoising method using dual-tree complex wavelet transform and Bernoulli-Gauss prior model. In estimating hyper-parameters for Bernoulli-Gaussian model, we present two simple and non-iterative methods. We use hypothesis-testing technique in order to estimate the mixing parameter, Bernoulli random variable. Based on the estimated mixing parameter, variance for clean signal is obtained by using maximum generalized marginal likelihood (MGML) estimator. We simulate our denoising method using dual-tree complex wavelet and compare our algorithm to well blown denoising schemes. Experimental results show that the proposed method can generate good denoising results for high frequency image with low computational cost.