• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.2
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• pp.281-288
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• 2011

In this paper, a variable quantization coefficient scanning for macroblock considering the histogram value of previous macroblock's quantization coefficient is proposed. In order to scan a quantization coefficient, the proposed method makes $4{\times}4$ histograms for various prediction modes($16{\times}16$, $16{\times}8$, $8{\times}16$, $8{\times}8$) by adding 1 if the value of quantization coefficient is not 0. After a final mode decision procedure, the $4{\times}4$ histogram of the final mode will be sorted. Then, quantization coefficients in corresponding macroblock of the next frame are scanned using the sorted order. The experimental results show that the proposed scheme reduces the total bits by approximately 0.01~2.25% with similar PSNR performance compared with the previous method.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.318-329
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• 1994

This paper deals with the finite wordlength effect on the performance of digital PID controllers. The finite wordlength, one of the major limitation factors in digital controllers, results on two kinds of quantization error : the signal quantization error and the coefficient quantization error. This paper derives the variance of the plant output due to the signal quantization error. Using stability margins as performance criterion, the statistical wordlength concept is adopted for coefficient wordlength selection. Finally, the experimental results exhibit satisfactory performance of the digital PID controller with statistical coefficient wordlength.

• ETRI Journal
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• v.33 no.5
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• pp.814-817
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• 2011

In this letter, the distributions of direct current (DC) coefficients for P-frames in H.264/AVC are analyzed, and the distortion model of the Gaussian source under the quantization of the dead-zone plus-uniform threshold quantization with uniform reconstruction quantizer is derived. Experimental results show that the DC coefficients of P-frames are best approximated by the Laplacian distribution and the Gaussian distribution at small quantization step sizes and at large quantization step sizes, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.477-482
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• 1989

In this paper, the effect of coefficient quantization error is analyzed for digital PID controllers. Stability margins are used as peformance criteria, and the statistical wordlength concept is adopted for coefficient wordlength selection. Finally, an illustrative example is given.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.296-305
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• 2000

In this paper, we propose the method of embedding the encrypted digital watermark in quantization coefficient when we encode the image data in the process of JPEC. The proposed method is as following. After a DCT coefficient of each block is quantized, we arrange the quantization coefficient as on dimension with a zigzag scan and replace each block. By applying even-odd feature of frequency of the encrypted watermark to a quantization coefficient of some fixed domain of replaced each block and embedding it, we obtain the compressed image data by encoding after placing it in the order prior to replacement. The advantages of the proposed method here are as follows: We can embed many information keeping a secret as much as possible by using the algorithm of block replacement. We can control the amount of embedding of each use, as we embed the encrypted information by selecting some fixed domain of a quantization coefficient, we can fix the embedding data regardless of the image and the value of quantization. We verified the results by experiments and analyzed the efficiency of them in comparison with the former study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.5
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• pp.364-373
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• 1990

When digital filters are implemented on a computer or with spectial purpose hardware, they unavoidably suffer from errors due to finite wordlength implementation. These errors are classified into coefficient quantiz ation error and roundoff error. The synthesizing method for realizations with minimum coefficient quantization error and minimum roundoff error has been studied. In this paper, it is shown that there is an equivalent transform relation between realizations with minimum coefficient quatization error and minimum roundoff error. To show tha validity of this equivalent transform, we derived the 2nd order digital filter with minimum coefficient quantization error from the 2nd order digital filter with minimum roundoff error and proved the efficiency of realization with minimum coefficient quantization error by simulation.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.36-42
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• 1997

This paper presents a new design technique for performing high quality low bit rate image compression. A hybrid coder(HC) which combines Mean Removed Important Coefficient Selection based JPEG(MR-ICS-JPEG) and Adaptive Vector Quantization (AVQ) is proposed. A new quantization table is developed using the Important Coefficient Selection(ICS) method; the importance of each coefficient is determined using the orthonormal property of the DCT. This quantization table is applied to standard JPEG with mean removal(MR) strategy before processing. This scheme, called MR-ICS-JPEG, produces more than 2 dB enhanced performance in terms of PSNR over standard JPEG. A set of homogeneous codebooks is generated by homogeneous training vectors. Before compression, an image is uniformly divided into 8${\times}$8 blocks. Low detail regions such as backgrounds are roughly coded by AVQ while high detail regions such as edges or curves are finely coded by the proposed MR-ICS-JPEG. This hybrid coder procuces consistently about 3 dB improved performance in terms of PSNR over standard JPEG.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.2
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• pp.155-165
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• 1990

The problem of quantization errors in digital filter design arises because of the practical necessity due to finite wordlength implementation. These errors are classified into coefficient quantization error and roung off error. In this paper, in order to analyze and reduce these errors, minimum ceefficient quantization realization is directly derived form impulse responese design specification. And using the equivalent transform relation between minimum coefficient quantization error and minimum roundoff error realizations, we synthesize an optimal realization state-space digital filter. This technique is analyzed by the simulation of an approximated 3rd model, which shows that it is superior to direct or cascade state-space digital filter in quantization errors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.56-63
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• 2009

Nowdays, Most of Internet Contents delivered as a compressed file. It gives many advantages like deduction of communication bandwidth and transmission time etc. In case of JPEG Compression, Quantization is the most important procedure which accomplish the compression. In general signal processing, Quantization is the process which converts continuous analog signal to discrete digital signal. As you known already, Quantization over JPEG compression is to reduce magnitude of pixel value in spatial domain or coefficient in frequency domain. A lot of Data Hiding algorithms also developed to applicable for those compressed files. In this paper, we are going to unveil the influence of quantization table which used in the process of JPEG compression. Even thought most of algorithm modify frequency coefficients with considering image quality, they are ignoring the influence of quantization factor corresponding with the modified frequency coefficient. If existing algorithm adapt this result, they can easily evaluate their performances.