• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.701-710
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• 2000

This paper presents a new method for an efficient coding of very low bit-rate color video based on adaptive wavelet transform. Our approach reveals that the coding process works more efficiently if the quantized wavelet coefficients are preprocessed by a mechanism exploiting the redundancies in the wavelet subband structure. Thus, we focuses optimized activity of coding part, and exhaustive overlapped block motion compensation is utilized to ensure coherency in motion compensated error frames, and raised cosine window is applied. The horizontal and vertical components of motion vectors are encoded separately using adaptive arithmetic coding while significant wavelet coefficients are encoded in bit-plane order using adaptive arithmetic coding. On average the proposed codec exceeds H.263 and ZTE in peak signal-to-noise ratio by as much as 2.07 and 1.38dB at 28 kbits, respectively. Fore entire sequence coding, 3DWCVC method is superior to H.263 and ZTE by 0.35 and 0.71dB on average, respectively.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.71-78
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• 2008

We propose a sub-band spreading technique for adaptive modulation (AM) in orthogonal frequency division multiplexing (OFDM) systems in order to reduce signaling overheads and to average frequency selective fading channels causing different signal-to-noise ratio (SNR) values for subcarriers in each subband. The conventional sub-band based AM schemes can also reduce signaling overheads and complexity for allocating a resource per sub-band at a time. However, they may suffer from the channel variation in a sub-band when the sub-band size is larger than the channel coherence bandwidth (BW). The sub-band spreading at the transmitter enables the received symbols in each sub-band to have an identical reliability even in a frequency selective fading channel. We rigorously analyze the averaged SNR value at the receiver of the sub-band spreading system and the analyzed average SNR in a sub-band is used for an adaptation criterion. The proposed AM scheme outperforms the conventional sub-band based OFDM scheme without spreading, and it can yield better throughput performance than the conventional subcarrier based AM schemes when we consider the signaling overheads.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.37-44
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• 2002

In this paper. we propose a new video coding scheme with multi-resolution motion compensation and residual quantization. The main functional blocks of the proposed scheme include multi-level wavelet decomposition. motion estimation and motion compensation. raster scanning within each subband. formation of block trees and blocking partitioning. and adaptive arithmetic coding. Although the proposed ceding scheme is simple and requires low computational complexity, it produces bitstreams tilth good features. such as the embedded structure and SNR scalability. Experimental results demonstrate that the proposed coding scheme is quote competitive to and often outperforms other wavelet-based video coding schemes in the literature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5078-5094
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• 2019

In recent years, the development of drone technologies has promoted the widespread commercial application of drones. However, the ability of drone to carry explosives and other destructive materials may bring serious threats to public safety. In order to reduce these threats from illegal drones, acoustic feature extraction and classification technologies are introduced for drone sound identification. In this paper, we introduce the acoustic feature vector extraction method of harmonic line association (HLA), and subband power feature extraction based on wavelet packet transform (WPT). We propose a feature vector extraction method based on combined HLA and WPT to extract more sophisticated characteristics of sound. Moreover, to identify drone sounds, support vector machine (SVM) classification with the optimized parameter by genetic algorithm (GA) is employed based on the extracted feature vector. Four drones' sounds and other kinds of sounds existing in outdoor environment are used to evaluate the performance of the proposed method. The experimental results show that with the proposed method, identification probability can achieve up to 100 % in trials, and robustness against noise is also significantly improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1424-1427
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• 2002

This paper proposes a novel postprocessing algorithm for reducing the blocking artifacts in low bit rate block-based transform coded images, that use adaptive neural network filter (NNF) in wavelet transform domain. n this algorithm, after performing a 2-level wavelet transform of the decompressed image, the existence of locking artifacts is determined using statistical characteristic of neighborhood blocks. And then a different one-dimensional (1-D) or 2-D NNF is used to reduce the locking artifacts according to the classified regions. That is, for HL and LH subbands regions with the blocking artifacts, a different 1-D NNF is used. And 2-D NNF is used in HH subband. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjectively and objectively.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1511-1514
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• 2002

This paper presents content adaptive image watermark embedding using stochastic visual model based on multiwavelet transform. To embedding watermark, the original image is decomposed into 4 levels using a discrete multiwavelet transform, then a watermark is embedded into the JND(just noticeable differences) of the image each subband. The perceptual model is applied with a stochastic approach fer watermark embedding. This is based on the computation of a NVF(noise visibility function) that have local image properties. The perceptual model with content adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the JND. This method uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The experiment results of simulation of the proposed watermark embedding method using stochastic visual model based on multiwavelet transform techniques was found to be excellent invisibility and robustness.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.94-102
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• 2007

In de-noising, it is wellknown that wavelet-thresholding algorithm shows near-optimal performances in the minimax sense. However, the wavelet-thresholding algorithm is difficult in realization it on hardware, such as FPGA, because of wavelet function complexity. In this paper, we present a new do-noising technique with the binary tree structured filter bank, which is based on the signal power ratio of each subbands to the total signal power. And we realize it on FPGA. For simple realization, the filter banks are designed by Hadamard transform coefficients. The simulation and hardware experimental results show that the performance of the proposed method is similar with that of soft thresholding de-noising algorithm based on wavelets, nevertheless it is simple.

• ETRI Journal
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• v.42 no.2
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• pp.217-229
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• 2020

Long-term electroencephalography (EEG) monitoring is time-consuming, and requires experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a novel automated method called adaptive slope of wavelet coefficient counts over various thresholds (ASCOT) to classify patient episodes as seizure waveforms. ASCOT involves extracting the feature matrix by calculating the mean slope of wavelet coefficient counts over various thresholds in each frequency subband. We validated our method using our own database and a public database to avoid overtuning. The experimental results show that the proposed method achieved a reliable and promising accuracy in both our own database (98.93%) and the public database (99.78%). Finally, we evaluated the performance of the method considering various window sizes. In conclusion, the proposed method achieved a reliable seizure detection performance with a short-term window size. Therefore, our method can be utilized to interpret long-term EEG results and detect momentary seizure waveforms in diagnostic systems.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3272-3279
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• 2000

In this paper, we propose two fast VQ coclebook search algorithms efficient to the Wavelet/ VQ coding schemes. It is well known that the probability having large values in wavelet coefficient blocks is very low. In order to apply this property to codebook search, the index tables of the reordered codebook in each wavelet subband ae used. The exil condition in PDE can be satisfied in an earlystage by comparing the large coefficients of the codeword with their corresponding elements of input vector using the index tbles. As a result, search time can be reduced.