• ETRI Journal
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• v.7 no.3
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• pp.12-16
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• 1985

In this paper, the basic philosophy and adaptation rule of adaptive quantization are described. By computer simulations, some properties of adaptive quantization for a first-order Gauss-Markov process are considered.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1234-1240
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• 2005

In this paper, I propose the wavelet image coding method using band adaptive quantization and the significant cluster extraction. The proposed method can reduce to unnecessary additional seed data which create on conventional MRWD coding, because it eliminate cluster which smaller than structuring element by using morphology. And it make fast coding possible, because it is reduced to computational complexity by using band adaptive quantization. Consequently, the proposed method reduces computational complexity with $20\%{\~}33.3\%$ according to bit rate in quantization process.

• ETRI Journal
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• v.23 no.1
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• pp.16-22
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• 2001

Efficient quantization methods of the line spectrum pairs (LSP) which have good performances, low complexity and memory are proposed. The adaptive quantization range method utilizing the ordering property of LSP parameters is used in a scalar quantizer and a vector-scalar hybrid quantizer. As the maximum quantization range of each LSP parameter is varied adaptively on the quantized value of the previous order's LSP parameter, efficient quantization methods can be obtained. The proposed scalar quantization algorithm needs 31 bits/frame, which is 3 bits less per frame than in the conventional scalar quantization method with interframe prediction to maintain the transparent quality of speech. The improved vector-scalar quantizer achieves an average spectral distortion of 1 dB using 26 bits/frame. The performances of proposed quantization methods are also evaluated in the transmission errors.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.85-90
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• 2004

This paper proposes the wavelet image coding using the significant cluster extraction by morphology and the adaptive quantization. In the conventional MRWD method, the additional seed data takes large potion of the total data bits. The proposed method extracts the significant cluster using morphology to improve the coding efficiency. In addition, the adaptive quantization is proposed to reduce the number of redundant comparative operations which are indispensably occurred in the MRWD quantization. The experimental result shows that the proposed algorithm has the improved coding efficiency and computational cost while preserving superior PSNR

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.114-115
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• 2019

This paper introduces an adaptive scalar quantization scheme for video coding technology. The method utilizes the property of the coefficient groups (CG) inside each transform block so that the dead-zone interval of the scalar quantizer is adaptively set up for different CGs. Its experimental results show that our proposed quantization scheme can achieve BDBR reduction of 4.75%, 5.93, and 5.16% for Y, Cb, and Cr channel respectively when encoding with HEVC.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.187-196
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• 2017

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.106-113
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• 1998

Quantizer with bit rate control performs lossy compressionin moving image coding. Efficient quantizer can improve subjective quality of reconstructed image at the same bit rate because most of errors are occured at this stage. Although quantization matix of current compression stantards reflects human visual system, the performance of their quantization matrixes is not always optimal because they are not considering each image characteristics. We proposed a new adaptive optimal quantization matrix obtained by considering complexity of each image subblocks. It resulted in improvments of image quality about 0.05-0.82 dB and good subject quality at edge regions when we simulated the quantization method in various coding statndards.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.6
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• pp.411-420
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• 1986

Quantization noise of nonadaptive Linear Delta Modulation(LDM) and adaptive Constant Factor Delta Modulation(CFDM) systems is studied. The formulas for quantization noise of CFDM system are derived on the basis of the rusults of LDM. And the output signal-to-quantization noise ratios(SNR) in LDM and CFDM systems are calculated in the range of bit rates from 16[Kb/s] to 96[Kb/s]. By comparing LDM and CFDM, it is known that the adaptive DM is superior to non-adaptive DM by 8[dB] when bit rate is 20[Kb/s] and SNR advantage increases to 14[dB] when bit rate is 56[Kb/s]. All the theoretical results agree well with the experimental results.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.672-680
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• 2010

This paper presents an adaptive quantization matrix selection scheme for H.264 video encoding. Conventional H.264 coding standard applies the same quantization matrix to the entire video sequence without considering local characteristics in each frame. In this paper, we propose block adaptive selection of quantization matrix according to edge directivity of each block. Firstly, edge directivity of each block is determined using intra prediction modes of its spatially adjacent blocks. If the block is decided as a directional block, new weighted quantization matrix is applied to the block. Otherwise, conventional quantization matrix is used for quantization of the non-directional block. Since the proposed weighted quantization is designed based on statistical distribution of transform coefficients in accordance with intra prediction modes, we can achieve high coding efficiency. Experimental results show that the proposed scheme can improve coding efficiency by about 2% in terms of BD bit-rate.