• ETRI Journal
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• v.29 no.1
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• pp.99-102
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• 2007

The channel level difference (CLD) is a main parameter in the reference model 0 (RM0) for MPEG Surround. Nevertheless, the CLD quantization method in the RM0 has problems such as the lack of theoretical background and inappropriate quantization levels. In this letter, a new CLD quantization method is proposed based on the virtual source location information which has strength in the quantization process. From experimental results, it is confirmed that the proposed scheme greatly reduces the quantization distortions measured in dB and degrees without any additional complexity.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.422-428
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• 2023

Ultrafast ultrasound imaging has been applied to various imaging approaches, including shear wave elastography, ultrafast Doppler, and super-resolution imaging. However, these methods are still challenging in real-time implementation for three Dimension (3D) or portable applications because of their massive data rate required. In this paper, we proposed an adaptive quantization method that effectively reduces the data rate of large Radio Frequency (RF) data. In soft tissue, ultrasound backscatter signals require a high dynamic range, and thus typical quantization used in the current systems uses the quantization level of 10 bits to 14 bits. To alleviate the quantization level to expand the application of ultrafast ultrasound imaging, this study proposed a depth-sectional quantization approach that reduces the quantization errors. For quantitative evaluation, Field II simulations, phantom experiments, and in vivo imaging were conducted and CNR, spatial resolution, and SSIM values were compared with the proposed method and fixed quantization method. We demonstrated that our proposed method is capable of effectively reducing the quantization level down to 3-bit while minimizing the image quality degradation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.133-138
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• 2015

This paper presents a performance improvement of gray level co-occurrence matrix(GLCM) based on the nonuniform quantization, which is generally used to analyze the texture of images. The nonuniform quantization is given by Lloyd algorithm of recursive technique by minimizing the mean square error. The nonlinear intensity levels by performing nonuniformly the quantization of image have been used to decrease the dimension of GLCM, that is applied to reduce the computation loads as a results of generating the GLCM and calculating the texture parameters by using GLCM. The proposed method has been applied to 30 images of $120{\times}120$ pixels with 256-gray level for analyzing the texture by calculating the 6 parameters, such as angular second moment, contrast, variance, entropy, correlation, inverse difference moment. The experimental results show that the proposed method has a superior computation time and memory to the conventional 256-level GLCM method without performing the quantization. Especially, 16-gray level by using the nonuniform quantization has the superior performance for analyzing textures to another levels of 48, 32, 12, and 8 levels.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.114-121
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• 2013

BTC image compression is a simple and easy hardware implementation, is widely used in a video compression techniques required for LCD overdrive. In this paper, methods for reducing compression loss, a multi-level quantization BTC (MLQ-BTC) algorithm is proposed. The process of the MLQ-BTC algorithm is, a input image is compressed and decompressed by Quasi 8-level method and Advanced 2-level BTC method, and select the algorithm with the smallest compression loss. Simulation results show that the proposed algorithm is efficient as compared with PSNR and compression ratio of the existing BTC methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.709-715
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• 2010

MCDD performs demultiplexing and demodulation of multi-carrier signals for signal processing schemes such as switching, channel encoding and remodulation in an OBP satellite. During the demultiplexing procedure, several factors such as frequency offset and/or quantization error degrade BER performance. Hence, influences of those factors should be reduced. A influence of the frequency offset can be reduced by inserting guard band between channels, and that of quantization error can be decreased by quantization level control. In case that the data rate of system is not limited, the guard band and the quantization level do not affect each other. In the other case, however, mutual influence between them should be considered. In this paper, we observe the mutual influence when the data rate of the MCDD is limited, and analyze the BER performance.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.187-190
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• 2001

In this paper, we present a novel digital watermarking technique based on the concept of multiresolution decomposition and Human Visual System(HVS). Proposed watermarking is to embed watermark by quantization, that is to construct ‘perceptually lossless’quantization matrix, by using a quantization factor for each level and orientation and variance within a band. We compare our approach with another wavelet domain watermarking methods. Simulation results show the superior performance of robustness for variety image distortions.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.185-193
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• 2009

This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1685-1695
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• 1996

The postprocessing of compressed images based on the projections onto convex sets and the constrained minimization imposes several constraints on the procesed data. The quantization constraint has been commonly used in various algorithms. Quantization is many-to-one mapping, by which all the dat in a quantization region are mapped to the corresponding representative level. The basic idea behind the projection onto the QCS(quantization constraint set) is to prevent the processed data from diverging from the original quantization region in order to redue the artifacts caused by filtering in postprocessing. However, there have been few efforts to analye the POQCS(projection onto the QCS). This paper analyzed mathematically the POQCS of filtered data from the viewpoint of minimizing the mean square error. Our analysis shows that a proper filtering technique followed by the POQCS can reduce the quantization distortion. In the conventional POQCS, the outside data of each quantization region are mapped into the corresponding boundary. Our analysis also shows that mappingthe outside data to the boundary of a subregion of the quantization region yields lower distortion than does the mapping to the boundary of the original region. In addition, several examples and discussions on the theory are introduced.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.662-665
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• 2001

As the fuzzy control is applied to servo system the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$-level set decomposition of fuzzy sets by quantize $\alpha$-cuts. This method can be easily implemented with analog hardware. The influence of quantization levels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of do servo system. It examined useful with experiment for dc servo system.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2783-2785
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• 2003

In multi-dimensional magnetic resonance imaging, data is obtained in the spatial frequency domain. Since the signal variation in the spatial frequency domain is much larger than that in the spatial domain, analog-to-digital converts with wide conversion bits are required. In this paper, the quantization noise in magnetic resonance imaging is analyzed. The signal-to-quantization noise ratio(SQNR) in the reconstructed image is derived from the level of quantization in the data acquisition. Since the quantization noise is proportional to the signal amplitude, it becomes more dominant in high field imaging. Using the derived formula the SQNR for several MRI systems are evaluated, and it is shown that the quantization noise can be a limiting factor in high field imaging, especially in three dimensional imaging in magnetic resonance imaging.