• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.27-37
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• 1991

This paper proposes the ESFVQ(energy subspace fuzzy vector quantization) that employs energy subspaces to reduce the quantizing distortion which is less than that of a fuzzy vector quatization. The ESFVQ is applied to a speaker adaptation method by which Korean words spoken by unknown speakers are recognized. By generating mapped codebooks with fuzzy histogram according to each energy subspace in the training procedure and by decoding a spoken word through the ESFVQ in the recognition proecedure, we attempt to improve the recognition rate. The performance of the ESFVQ is evaluated by measuring the quantizing distortion and the speaker adaptive recognition rate for DDD telephone area names uttered by 2 males and 1 female. The quatizing distortion of the ESFVQ is reduced by 22% than that of a vector quantization and by 5% than that of a fuzzy vector quantization, and the speaker adaptive recognition rate of the ESFVQ is increased by 26% than that without a speaker adaptation and by 11% than that of a vector quantization.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.79-86
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• 2003

A new quantization constraint set based on the theory of Projection onto Convex Set(POCS) is proposed to reduce blocking artifact appearing in block-coded images. POCS-based postprocessing for alleviating the blocking artifact consists of iterative projections onto smoothness constraint set and quantization constraint set, respectively. In general, the conventional quantization constraint set has the maximum size of range where original image data can be included, therefore over-blurring of restored image is unavoidable as iteration proceeds. The projection onto the proposed quantization constraint set can reduce blocking artifact as well as maintain the clearness of the decoded image, since it controls adaptively the size of quantization constraint set according to the DCT coefficients. Simulation results using the proposed quantization constraint set as a substitute for conventional quantization constraint set show that the blocking artifact of the decoded image can be reduced by the small number of iterations, and we know that the postprocessed image maintains the distinction of the decoded image.

• 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.

• 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.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.291-294
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• 2000

본 논문에서는 웨이브릿 변환영역에서 개선된 모폴로지와 적응양자화를 이용한 영상부호화 방법을 제안한다 제안한 방법은 제로트리를 기반으로 한 기존의 방법들과 유사한 코딩성능을 가지면서 EZW, SFQ 등에서 나타나는 복잡성을 모폴로지를 사용하여 유효정보를 클러스터링 함으로써 복잡성을 줄일 수 있다. 그러나 클러스터의 개수가 많아지면 클러스터를 나타내는 부가정보의 양도 많아진다. 이러한 부가정보의 비율이 실제데이터에서 많은 비중을 차지하기 때문에 개선된 모폴로지를 적용하여 효율적으로 부호화 함으로써 영상의 화질을 개선하였다. 또한 고주파 대역에서의 유효계수를 효율적으로 코딩하기 위해 적응양자화를 적용하여 양자화 시 오차범위를 줄일 수 있다. 따라서 제안한 방법은 양자화 시 발생하는 많은 비교연산을 줄일 수 있으며, 기존의 방법에 비해 화질을 개선하였다.

• 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 Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.18-27
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• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure and various quantization algorithms are proposed depending on the lattice. In this paper, such a lattice vector quantization is implemented by using the sample-adaptive product quantizer (SAPQ). It is shown that several important lattices can be implemented by SAPQ and the lattice vector quantization can be performed by using a simple integer-transform function of scalar values within SAPQ. The performance of the proposed lattice SAPQ is compared to the entropy-constrained scalar quantizer and the entropy-constrained SAPQ (ECSAPQ) at a similar encoding complexity. Even though ECSAPQ shows a good performance at low bit-rates, lattice SAPQ shows better performance than the ECSAPQ case for a wide range of bit rates.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.67-75
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• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure, and various quantization algorithms are proposed depending on the lattice. Such a lattice vector quantizer (VQ) can be implemented by using the sample-adaptive product quantizer (SAPQ) and its output can also be easily entropy encoded. In this paper, the entropy encoding scheme for the lattice VQ is proposed based on SAPQ, and the performance of the proposed lattice VQ, which is based on SAPQ with the entropy coder, is asymptotically compared as the rate increases. It is shown by experiment that the gain for the memoryless Gaussian source also approaches the theoretic gain for the uniform density case.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.191-194
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• 1997

본 논문에서는 2D-DCT 변환된 동영상 프레임 사이의 오차 블록들의 활성 레벨(atcivity level)과 에지의 특성을 분류하여 동영상의 적응적인 양자화를 제안한다. 각 블록에서는 활성 레벨이 각기 다르고, 같은 활성 레벨이라 할지라도 에지의 특성도 각기 다르게 나타난다. 적응적인 양자화를 위해서, 2D-DCT 변환된 영상 오차의 각 블록의 활성레벨 뿐만 아니라 AC 계수들의 분포에 따른 에지 특성을 분류하면, 블록의 활성 레벨만을 일률적으로 적용한 Sorting 방법의 경우보다 향상된 영상을 복원할 수 있다. 블록의 활성 레벨은 AC energy에 의해서 측정하고, 에지 특성은 AC 계수들의 분포에 의해 결정하게 된다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.5
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• pp.42-47
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• 1999

연속 계조도 영상을 이진 영상(하프톤 영상)으로 변환하는 하프톤 기법중 대표적인 두 방법은 순차적 디더법과 오차 확산법이 있다. 이 중에서 오차확산법은 예리한 하프톤 영상을 얻기위한 우수한 하프톤 기법으로 잘 알려져 있다. 그러나 알고리듬에 기인하는 여러 인공잡음들이 발생하므로 이를 개선하기 위한 방법으로 최적의 필터 계수를 얻기 위한 많은 연구가 진행되었다. 본 논문에서는 연속 계조도 입력 영상과 하프톤 영상사이의 양자화 오차를 영상에 적응적이며 최적으로 확산시키기 위해 양자화 오차를 초기 가능성의 퍼지 부분 집합으로 정의하였다. 이러한 퍼지 부분 집합의 중심화소에 대해 이웃한 화소의 오차 가능성을 고려한 후 FAM 규칙을 이용하여 각각 화소들의 오차 가능성을 영상에 따라 적응적으로 갱신하였으며 이를 원영상에 더하여 다시 양자화 과정을 번복하는 퍼지 이완 알고리듬을 이용한 오차 확산법을 제안하였다. 제안한 방법을 이용하여 얻은 결과를 최적 필터 계수를 구하기 위한 기존의 방법의 결과 영상과 비교 분석하였다.