• 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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2817-2834
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• 2016

The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.53-62
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• 2013

Cloud environment is one in the field of distributed computing and it consists of physical nodes and virtual nodes. In distributed cloud environment, an optimal path search is that each node to perform a search for an optimal path. Synchronization of each node is required for the optimal path search via fast data transmission because of real-time environment. Therefore, a quantization technique is required in order to guarantee QoS(Quality of Service) and search an optimal path. The quantization technique speeds search data transmission of each node. So a main server can transfer data of real-time environment to each node quickly and the nodes can perform to search optimal paths smoothly. In this paper, we propose the quantization technique to solve the search problem. The quantization technique can reduce the total data transmission. In order to experiment the optimal path search system which applied the quantized data transmission, we construct a simulation of cloud environment. Quantization applied cloud environment reduces the amount of data that transferred, and then QoS of an application for the optimal path search problem is guaranteed.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1347-1351
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• 1987

This thesis aims at studying laplacian pyramid vector quantization which keeps a simple compression algorithm and stability against various kinds of image data. To this end, images are devied into two groups according to their statistical characteristics. At 0.860 bits/pixel and 0.360 bits/pixel respectively, laplacian pyramid vector quantization is compared to the existing spatial domain vector quantization and transform coding under the same condition in both objective and subjective value. The laplacian pyramid vector quantization is much more stable against the statistical characteristics of images than the existing vector quantization and transform coding.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.11
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• pp.20-28
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• 1997

In this paper, quantization and inverse quantizatio unit, a sa component of MPEG-2 moving picture compression system, ar edesigned. In the processing of quantization, this design adopted newly designed arithmetic units in which quantization matrices and scale code was expressed with SD(signed-digit) code. In the arithmetic unit of inverse quantization, quantization scale code, which has 5-bits length, is splited into two pieces; 2-bits for control code, 3-bits for quantization data, and the method to devise quantization step size is proposed. The design was coded with VHDL and synthesis results in that it consumed about 6,110 gates, and operating speed is 52MHz.

• Communications of the Korean Mathematical Society
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• v.38 no.2
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• pp.431-450
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• 2023

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus to make an approximation of a continuous probability distribution by a discrete distribution. It has broad application in signal processing and data compression. In this paper, first we define the uniform distributions on different curves such as a line segment, a circle, and the boundary of an equilateral triangle. Then, we give the exact formulas to determine the optimal sets of n-means and the nth quantization errors for different values of n with respect to the uniform distributions defined on the curves. In each case, we further calculate the quantization dimension and show that it is equal to the dimension of the object; and the quantization coefficient exists as a finite positive number. This supports the well-known result of Bucklew and Wise [2], which says that for a Borel probability measure P with non-vanishing absolutely continuous part the quantization coefficient exists as a finite positive number.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.135-141
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• 2012

To reduce frame memory size usage in LCD overdrive, block truncation coding (BTC) image compression is commonly used. For maximization of compression ratio, BTC image compression is need to compress bitmap or quantization data. In this paper, for high compression ratio, we propose CMBQ-BTC (CMBQ : compression method bitmap data and quantization data) algorithm. Experimental results show that proposed algorithm is efficient as compared with PSNR and compression ratio of the conventional BTC method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.2
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• pp.100-106
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• 2010

The impact of surface quantization on device parameters of a Si metal oxide semiconductor (MOS) capacitor has been analyzed in the present work. Variation of conduction band bending, position of discrete energy states, variation of surface potential, and the variation of inversion carrier concentration at charge centroid have been analyzed for different gate voltages, substrate doping concentrations and oxide thicknesses. Oxide thickness calculated from the experimental C-V data of a MOS capacitor is different from the actual oxide thickness, since such data include the effect of surface quantization. A correction factor has been developed considering the effect of charge centroid in presence of surface quantization at strong inversion and it has been observed that the correction due to surface quantization is crucial for highly doped substrate with thinner gate oxide.