• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.517-529
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• 2011

In this paper, the parameters of the RTT (Radio Transmission Techniques) for SANET (Ship Ad-hoc NETwork), which is considered for the next generation maritime communication systems, are set up. A channel model has been analyzed based on the practical measured maritime wireless channel in VHF (Very-High Frequency) for SANET system. Also, by considering the frame structure including preamble, guard time and pilots for both single and multi-carrier systems, the BER (Bit Error Rate) performances are evaluated and analyzed in the aspects of channel compensation and channel coding techniques. Based on the simulation results, optimal modulation & coding schemes are suggested for SANET. That is, in single-carrier system by using differential modulation schemes, channel compensation is not necessary. However, channel coding is helpful to achieve additional gain. On the other hand, when 16-QAM modulation is employed in multi-carrier system, the implementation of both channel compensation and channel coding techniques show huge performance gain for various of K values, which are related to different maritime environments, and the rolling effects of wave.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.127-132
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• 2006

Quantization in video coding plays an important role in controlling the bit-rate of compressed video bit-streams. It has been used as an important control means to adjust the amount of bit-streams to at]owed bandwidth of delivery networks and storage. Due to the dependent nature of video coding, dependent quantization has been proposed and applied for MPEG-2 video coding to better maintain the quality of reconstructed frame for given constraints of target bit-rate. Since Scalable Video Coding (SVC) being currently standardized exhibits highly dependent coding nature not only between frames but also lower and higher scalability layers where the dependent quantization can be effectively applied, in this paper, we propose a dependent quantization scheme for SVC and compare its performance in visual qualities and bit-rates with the current JSVM reference software for SVC. The proposed technique exploits the frame dependences within each GOP of SVC scalability layers to formulate dependent quantization. We utilize Lagrange optimization, which is widely accepted in R-D (rate-distortion) based optimization, and construct trellis graph to find the optimal cost path in the trellis by minimizing the R-D cost. The optimal cost path in the trellis graph is the optimal set of quantization parameters (QP) for frames within a GOP. In order to reduce the complexity, we employ pruning procedure using monotonicity property in the trellis optimization and cut the frame dependency into one GOP to decrease dependency depth. The optimal Lagrange multiplier that is used for SVC is equal to H.264/AVC which is also used in the mode prediction of the JSVM reference software. The experimental result shows that the dependent quantization outperforms the current JSVM reference software encoder which actually takes a linear increasing QP in temporal scalability layers. The superiority of the dependent quantization is achieved up to 1.25 dB increment in PSNR values and 20% bits saving for the enhancement layer of SVC.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.68-77
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• 2000

Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.620-623
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• 1988

A vowel is based on the recognition of a phoneme. Thus it is necessary for the programming of an algorithm to achieve the speech recognition in that case. In this paper, cepstrum is used for a voiced-unvoiced decision and speech parameters are extracted by linear prediction coding. Using these parameters, a speech understanding algorithm has been developed.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.241-242
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• 2006

MPEG Surround is an audio coding technology that represents multi-channel audio signal with downmixed audio signal(s) and very low bitrate side information based on Binaural Cue Coding. The side information consists of Inter-Channel Level Difference, Inter-Channel Correlation, and payloads. These two parameters are correspondent to the well-known spatial parameters in psycho-acoustics, Inter-aural Level Difference (ILD) and Inter-Aural Cross Correlation (IACC). Though ICLD is to provide perceptually equivalent ILD to the listener, however, the ILD of the original multi-channel audio signal and that of the MPEG Surround encoded signal was different. The difference between two ILD values is defined as ILD Distortion (ILDD). This paper provides how ILDD can be applied to enhance sound quality in MPEG Surround and how much ILDD is decreased.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.218-226
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• 2001

The MPEG-2 Test Model 5 (TM5) algorithm is widely used for bit rate control. In TM5, however, the target number of bits and the number of actual coding bits for each picture do not match well. Therefore, buffer overflow and picture quality degradation may occur at the end of the GOP. In this paper, we propose a new bit rate control algorithm for matching the target and the actual coding bits based on accurate bit allocation. The key idea of the proposed algorithm is to determine quantization Parameters which enable us to generate the number of actual coding bits close to the target number of bits for each picture, while maintaining uniform picture quality and supporting real-time processing. The proposed algorithm exploits the relationship between the number of actual coding bits and the number of estimated bits of the previous macroblock.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1134-1142
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• 2019

Detection of double compression is one of the most efficient ways of remarking the validity of videos. Many methods have been introduced to detect HEVC double compression with different coding parameters. However, HEVC double compression detection under the same coding environments is still a challenging task in video forensic. In this paper, we introduce a novel method based on the frame partitioning information in intra prediction mode for detecting double compression in with the same coding environments. We propose to extract statistical feature and Deep Convolution Neural Network (DCNN) feature from the difference of partitioning picture including Coding Unit (CU) and Transform Unit (TU) information. Finally, a softmax layer is integrated to perform the classification of the videos into single and double compression by combing the statistical and the DCNN features. Experimental results show the effectiveness of the statistical and the DCNN features with an average accuracy of 87.5% for WVGA and 84.1% for HD dataset.

• Current Optics and Photonics
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• v.7 no.1
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• pp.1-14
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• 2023

Wavefront-coding imaging can achieve high-quality imaging along with a wide range of defocus. In this paper, the anti-laser detection and damage performance of wavefront-coding imaging systems using different asymmetric phase masks are studied, through modeling and simulation. Based on FresnelKirchhoff diffraction theory, the laser-propagation model of the wavefront-coding imaging system is established. The model uses defocus distance rather than wave aberration to characterize the degree of defocus of an imaging system. Then, based on a given defocus range, an optimization method based on Fisher information is used to determine the optimal phase-mask parameters. Finally, the anti-laser detection and damage performance of asymmetric phase masks at different defocus distances and propagation distances are simulated and analyzed. When studying the influence of defocus distance, compared to conventional imaging, the maximum single-pixel receiving power and echo-detection receiving power of asymmetric phase masks are reduced by about one and two orders of magnitude respectively. When exploring the influence of propagation distance, the maximum single-pixel receiving power of asymmetric phase masks decreases by about one order of magnitude and remains stable, and the echodetection receiving power gradually decreases with increasing propagation distance, until it approaches zero.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.35-41
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• 2002

There are many image segmentation methods having been published as the results of research so far, but it is difficult to be partitioned to each similar range that should be extracted into the accurate parameters of image information on the images with noises. Also if it is used to fractal coding, according to amount of noise in image, the image segmentation leads to decreasing of the compression ratio. In this paper, we propose the new quad-tree image segmentation using the box-counting dimension which can estimate the effective image information parameters against the noise properties and apply this method to fractal image coding. As the result of simulation, we confirm that the image segmentation is improved to 31.10% for parameter detection of image information and compression ratio is enhanced to 38.93% for fractal image coding when tested on 10% Gaussian white noise image by the proposed quad-tree method compared with method using existing quad-tree. 

• The Journal of the Acoustical Society of Korea
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• v.31 no.2
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• pp.93-99
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• 2012

For speech coding, a vocal tract is modeled using Linear Predictive Coding (LPC) coefficients. The LPC coefficients are typically transformed to Line Spectral Frequency (LSF) parameters which are advantageous for linear interpolation and quantization. If multidimensional LSF data are quantized directly using Vector-Quantization (VQ), high rate-distortion performance can be obtained by fully utilizing intra-frame correlation. In practice, since this direct VQ system cannot be used due to high computational complexity and memory requirement, Split VQ (SVQ) is used where a multidimensional vector is split into multilple sub-vectors for quantization. The LSF parameters also have high inter-frame correlation, and thus Predictive SVQ (PSVQ) is utilized. PSVQ provides better rate-distortion performance than SVQ. In this paper, to implement the optimal predictors in PSVQ for voice storage devices, we propose Multi-Frame AR-model based SVQ (MF-AR-SVQ) that considers the inter-frame correlations with multiple previous frames. Compared with conventional PSVQ, the proposed MF-AR-SVQ provides 1 bit gain in terms of spectral distortion without significant increase in complexity and memory requirement.