• Title/Summary/Keyword: quantized system

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Off-line recognition of handwritten korean and alphanumeric characters using hidden markov models (Hidden Markov Model을 이용한 필기체 한글 및 영.숫자 오프라인 인식)

  • 김우성;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.9
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    • pp.85-100
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    • 1994
  • This paper proposes a recognition system of constrained handwritten Hangul and alphanumeric characters using discrete hidden Markov models (HMM). HMM process encodes the distortion and similarity among patterns of a class through a doubly stochastic approach. Characterizing the statistical properties of characters using selected features, a recognition system can be implemented by absorbing possible variations in the form. Hangul shapes are classified into six types by fuzzy inference, and their recognition is performed based on quantized features by optimally ordering features according to their effectiveness in each class. The constrained alphanumerics recognition is also performed using the same features used in Hangul recognition. The forward-backward, Viterbi, and Baum-Welch reestimation algorithms are used for training and recognition of handwritten Hangul and alphanumeric characters. Simulation result shows that the proposed method recognizes handwritten Korean characters and alphanumerics effectively.

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Quantized CNN-based Super-Resolution Method for Compressed Image Reconstruction (압축된 영상 복원을 위한 양자화된 CNN 기반 초해상화 기법)

  • Kim, Yongwoo;Lee, Jonghwan
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.4
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    • pp.71-76
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    • 2020
  • In this paper, we propose a super-resolution method that reconstructs compressed low-resolution images into high-resolution images. We propose a CNN model with a small number of parameters, and even if quantization is applied to the proposed model, super-resolution can be implemented without deteriorating the image quality. To further improve the quality of the compressed low-resolution image, a new degradation model was proposed instead of the existing bicubic degradation model. The proposed degradation model is used only in the training process and can be applied by changing only the parameter values to the original CNN model. In the super-resolution image applying the proposed degradation model, visual artifacts caused by image compression were effectively removed. As a result, our proposed method generates higher PSNR values at compressed images and shows better visual quality, compared to conventional CNN-based SR methods.

Performance Improvement of Downlink Real-Time Traffic Transmission Using MIMO-OFDMA Systems Based on Beamforming (Beamforming 기반 MIMO-OFDMA 시스템을 이용한 하향링크 실시간 트래픽 전송 성능 개선)

  • Yang Suck-Chel;Park Dae-Jin;Shin Yo-An
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.3 s.345
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    • pp.1-9
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    • 2006
  • In this paper, we propose a MIMO-OFDMA (Multi Input Multi Output-Orthogonal Frequency Division Multiple Access) system based on beamforming for performance improvement of downlink real-time traffic transmission in harsh channel conditions with low CIR (Carrier-to-Interference Ratio). In the proposed system, we first consider the M-GTA-SBA (Modified-Grouped Transmit Antenna-Simple Bit Allocation) using effective CSI (Channel State Information) calculation procedure based on spatial resource grouping, which is adequate for the combination of MRT (Maximum Ratio Transmission) in the transmitter and MRC (Maximum Ratio Combining) in the receiver. In addition, to reduce feedback information for the beamforming, we also apply QEGT (Quantized Equal Gain Transmission) based on quantization of amplitudes and phases of beam weights. Furthermore, considering multi-user environments, we propose the P-SRA (Proposed-Simple Resource Allocation) algorithm for fair and efficient resource allocation. Simulation results reveal that the proposed MIMO-OFDMA system achieves significant improvement of spectral efficiency in low CRI region as compared to a typical open-loop MIMO-OFDMA system using pseudo-orthogonal space time block code and H-ARQ IR (Hybrid-Automatic Repeat Request Incremental Redundancy).

Error Analysis for Optical Security by means of 4-Step Phase-Shifting Digital Holography

  • Lee, Hyun-Jin;Gil, Sang-Keun
    • Journal of the Optical Society of Korea
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    • v.10 no.3
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    • pp.118-123
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    • 2006
  • We present an optical security method for binary data information by using 4-step phase-shifting digital holography and we analyze tolerance error for the decrypted data. 4-step phase-shifting digital holograms are acquired by moving the PZT mirror with equidistant phase steps of ${\pi}/2$ in the Mach-Zender type interferometer. The digital hologram in this method is a Fourier transform hologram and is quantized with 256 gray level. The decryption performance of the binary data information is analyzed. One of the most important errors is the quantization error in detecting the hologram intensity on CCD. The greater the number of quantization error pixels and the variation of gray level increase, the more the number of error bits increases for decryption. Computer experiments show the results for encryption and decryption with the proposed method and show the graph to analyze the tolerance of the quantization error in the system.

Multiple Description Coding using Unequal MDSQ in Wavelet Domain

  • Yoon, Eung-Sik;Park, Kwang-Pyo;Lee, Keun-Young
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.281-284
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    • 2002
  • Error resilience for image coding is an important component of multimedia communication system. Error resilience schemes address loss recovery from the compression perspective. Multiple description coding (MDC) is one of the error resilience techniques promising for robust video transmission. It is the way to achieve tradeoff description such as scalar quantization, correlating transform and the quantized frame expansion. In this paper, we consider Multiple Description Scalar Quantization (MDSQ) to wavelet domain. Conventional MDSQ schemes considered description with equal weights in each sub-bands. But, we can see that the each sub-bands is unequal contribution to whole image quality. Therefore, we experiment the multiple design MDSQ table to make probability of zero index high, which gives high efficiency in arithmetic symbol coder. We also compare our proposed method with the conventional methods and show improved performance in terms of redundancy-rate-distortion.

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Weighted Distance-Based Quantization for Distributed Estimation

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.12 no.4
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    • pp.215-220
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    • 2014
  • We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

A DCT-Based Bisually Adaptive Quantization (DCT 기반의 시각 적응적 양자화 방법에 관한 연구)

  • Park, Sung-Chan;Kim, Jung-Hyun;Lee, Guee-Sang
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.7
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    • pp.332-338
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    • 2001
  • A visually adaptive quantization method of DCT-based images based on Human Visual System(HVS) is proposed. This approach uses the spatial masking in HVS characteristics to obtain higher compression ratio with relatively small degradation in the image quality. HVS is nonsensitive to an edge area, so a high complexity area is quantized coarsely in contrast to fine quantization of the low complexity area. The complexity of an area is estimated by the variance of DCT coefficients of the image. Experimental results demonstrate the performance of the proposed method and the resulting images show little difference from the original image in the subjective perception.

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A New Proposal of Extended BTC for Picture Data Compression (영상압축을 위한 확장된 BTC의 새로운 제안)

  • 고형화;이충웅
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.1
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    • pp.81-87
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    • 1988
  • This paper proposes a new EBTC(extended block truncation coding) algorithm extended from the BTC for image compression. The EBTC has a capability to eliminate the defects of BTC, such as the deterioration of resolution or blocky effect,and to make a real-time processing like BTC. It shows better performances than the DPCM and the transform coding. Especially, it is a suitable coding method for the high quality picture transmission. It may be adequate to the system of transmission rate of 30-50 Mbits/sec. The picture quality has been scarecely degraded with a vector quantization to the EBTC output at the bit rate of 1.25 bits/pel. The bit rate of the scalar quantized EBTC method is 2.6-3.7 bits/pel.

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An Efficient Requantization for Transcoding of MPEG Video

  • Hwang, Hee-Chul;Kim, Duk-Gyoo
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1023-1026
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    • 2002
  • In this paper, we propose an efficient transcoding of MPEG video. Transcoding is the process of converting a compressed video format to another different compressed video format. We propose an simple and efficient transcoding by requantization in which MPEG coded video at high bit-rate is converted into MPEG bitstream at lower bit-rate. To reduce a image quality degradation, we use HVS(Human Visual System) that is the effect that visibility of noise is less in high activity regions than in low activity regions. By using the effect, the part of image in high activity region is coarsely quantized without seriously degrading the image quality. Experimental results show that the proposed method can provide good performance.

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Adaptive coding algorithm using quantizer vector codebook in HDTV (양자화기 벡터 코드북을 이용한 HDTV 영상 적응 부호화)

  • 김익환;최진수;박광춘;박길흠;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.10
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    • pp.130-139
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    • 1994
  • Video compression algorithms are based on removing spatial and/or temproal redundancy inherent in image sequences by predictive(DPCM) encoding, transform encoding, or a combination of predictive and transform encoding. In this paper, each 8$\times$8 DCT coefficient of DFD(displaced frame difference) is adaptively quantized by one of the four quantizers depending on total distortion level, which is determined by characteristics of HVS(human visual system) and buffer status. Therefore, the number of possible quantizer selection vectors(patterns) is 4$^{64}$. If this vectors are coded, toomany bits are required. Thus, the quantizer selection vectors are limited to 2048 for Y and 512 for each U, V by the proposed method using SWAD(sum of weighted absolute difference) for discriminating vectors. The computer simulation results, using the codebook vectors which are made by the proposed method, show that the subjective and objective image quality (PSNR) are goor with the limited bit allocation. (17Mbps)

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