• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2382-2390
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• 1999

In this paper, we employed a new quantization scheme called sample-adaptive product quantizer (SAPQ) to quantize image data based on the differential pulse code modulation (DPCM) coder, which has fixed length outputs and high bit rates. In order to improve the performance of traditional DPCM coders, the scalar quantizer should be replaced by the vector quantizer (VQ). As the bit rate increases, it will be nearly impossible to implement a conventional VQ or modified VQ, such as the tree-structured VQ, even if the modified VQ can significantly reduce the encoding complexity. SAPQ has a form of the feed-forward adaptive scalar quantizer having a short adaptation period. However, since SAPQ is a structurally constrained VQ, SAPQ can achieve VQ-level performance with a low encoding complexity. Since SAPQ has a scalar quantizer structure, by using the traditional scalar value predictors, we can easily apply SAPQ to DPCM coders. For synthetic data and real images, by employing SAPQ as the quantizer part of DPCM coders, we obtained a 2~3 dB improvement over the DPCM coders, which are based on the Lloyd-Max scalar quantizers, for data rates above 4 b/point.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.81-90
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• 2005

When we transmit signals, which are quantized by the vector quantizer (VQ), through noisy channels, the overall performance of the coding system is very dependent on the employed quantization scheme and the channel error effect. In order to design an optimal coding system, the source and channel coding scheme should be jointly optimized as in the channel-optimized VQ. As a suboptimal approach, we may consider the robust VQ (RVQ). In RVQ, we consider developing an index assignment function for mapping the output of quantizers to channel symbols so that the effect of the channel errors is minimized. Recently, a VQ, which can reduce the encoding complexity and is called the sample-adaptive product quantizer (SAPQ), has been proposed. SAPQ has very similar quantizer structure as to the product quantizer (PQ). However, the quantization performance can be better than PQ. Further, the encoding complexity and the memory requirement for the codebooks are lower than the regular full-search VQ case. In this paper, SAPQ is employed in order to design an RVQ to channel errors by reducing the vector dimension. Discussions on the codebook structure of SAPQ and experiments are introduced in an aspect of robustness to noisy channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1518-1531
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• 1999

The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1447-1454
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• 2014

In H.264 standard, an intra frame is the first frame of a GOP (Group of Pictures) and all macroblocks of an intra frame are encoded using the same quantization parameter. In addition, an intra frame is used for encoding the following frames of the same GOP so the encoding results of an intra frame affect the encoding results of the entire GOP. Thus, it is important to find the optimal quantization parameter of an intra frame for improving the quality of a GOP. In this paper, we propose an searching method for an optimal quantization parameter of an intra frame in real time. The proposed method uses a gradient descent method to find the optimal value based on characteristics of the optimal quantization parameters. Experimental results show that the proposed method captures the characteristics of the optimal quantization parameter and accurately estimates the optimal value.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.89-95
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• 2009

H.264/AVC is the state-of-the-art video compression standard which achieves high coding efficiency compared with the previous standards. H.264/AVC adopts zig-zag scanning in order to encode quantized transform coefficients in a block. However, its performance is not satisfactory because all blocks are scanned in the fixed order without considering the characteristics of blocks. This paper presents an adaptive coefficient scanning method for improving inter coding efficiency in H.264/AVC. In the proposed method, the coefficient scanning order for each prediction mode is adaptively controlled based on the information of previously-coded blocks. The experimental results show that the proposed coefficient scanning method improves the coding efficiency about 2.29% for high-quality HD sequences.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.219-227
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• 2009

In H.264/AVC, if each block is quantized with a adaptive quantization parameter(QP) regardless of the characteristics of a block, it could be the deterioration of the picture quality. In this paper, an adaptive block-based QP selection method is proposed in order to improve picture quality by utilizing the bit amounts of the zigzag-scanned integer transform coefficients of the neighboring blocks and changing the QP value in the current block. The proposed method works in the same way as the encoder and decoder without transmitting the change of QP value to the decoder side. The experimental results show that the proposed method achieves a gain of about $0.1\sim0.3dB$ compared with H.264/AVC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.286-291
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• 2003

In this Paper, we designed an LSP(Line Spectral Pairs) parameter quantizer with cascaded structure of vector quantizer and scalar quantizer for the wideband speech coder. We have chosen the 16th-order of the LP coefficients. These coefficients are then transformed into the LSP parameters which have the excellent properties for quantization and easy stability checking condition of synthesis filter. In the first stage of quantization, input LSP parameters are split-vector-quantized using two 8-th order codebooks. In the second stage, the components of residual vector are individually quantized by the scalar quantizer utilizing the ordering property of LSP parameters. The designed adaptive VQ-SQ quantizer using 35 bits/frame shows the wideband transparency that the average spectral distortion should be less than 1.6 ㏈ and less than 4% of the frames should have SD above 3 ㏈. The simulation results show that the designed quantizer provides a 2-3 bits/frame saving over the typical vector-scalar quantizer.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.64-67
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• 2020

최근 다양한 분야에서 딥 러닝 기반의 많은 연구가 진행되고 있으며 이에 따라 딥 러닝 모델의 경량화를 통해 제한된 메모리를 가진 하드웨어에 올릴 수 있는 경량화 된 딥 뉴럴 네트워크(DNN)를 개발하는 연구도 활발해졌다. 이에 본 논문은 주파수 영역에서의 군집화 기반 계층별 딥 뉴럴 네트워크 압축을 제안한다. 이산 코사인 변환, 양자화, 군집화, 적응적 엔트로피 코딩 과정을 각 모델의 계층에 순차적으로 적용하여 DNN이 차지하는 메모리를 줄인다. 제안한 알고리즘을 통해 VGG16을 손실률은 1% 미만의 손실에서 전체 가중치를 3.98%까지 압축, 약 25배가량 경량화 할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11b
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• pp.1075-1078
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• 2002

스트림 암호 시스템에서는 비선형 결합 LFSR 키 수열을 이용하였다. 주기가 존재하고 상관관계 공격에 약한 비선형 LFSR 키 수열의 문제를 개선하기 위해 제안된 카오스 키 수열은 균형성과 랜덤특성을 만족하지 못하고 있다. 따라서, 본 연구에서는 적응적 임계값 적용 방법을 이용하여 균형성과 랜덤특성을 만족하는 카오스 키 수열 생성 기법을 제안하였다. 본 연구에서 제안한 키 수열 생성 기법은 로지스틱 방정식을 이용하여 키 수열 생성을 위한 카오스 신호를 만든 다음 카오스 신호를 적응적 임계값 적용방법을 통해 '0'과 '1'로 양자화하여 키 수열을 생성한다. 제안한 알고리즘으로 생성된 키 수열의 특징을 분석한 결과 균형성과 랜덤특성이 기존의 카오스 키 수열에 비해 개선되었음을 알 수 있다.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1149-1158
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• 2003

Content adaptive watermark embedding algorithm using a stochastic image model in the multiwavelet transform is proposed in this paper. A watermark is embedded into the perceptually significant coefficients (PSCs) of each subband using multiwavelet transform. The PSCs in high frequency subband are selected by SSQ, that is, by setting the thresholds as the one half of the largest coefficient in each subband. The perceptual model is applied with a stochastic approach based on noise visibility function (NVF) that has local image properties for watermark embedding. This model uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The watermark estimation use shape parameter and variance of subband region. it is derive content adaptive criteria according to edge and texture, and flat region. The experiment results of the proposed watermark embedding method based on multiwavelet transform techniques were found to be excellent invisibility and robustness.