• Title/Summary/Keyword: Spectral coding

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Region-based Spectral Correlation Estimator for Color Image Coding (컬러 영상 부호화를 위한 영역 기반 스펙트럴 상관 추정기)

  • Kwak, Noyoon
    • Journal of Digital Contents Society
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    • v.17 no.6
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    • pp.593-601
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    • 2016
  • This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

Block Constrained Trellis Coded Vector Quantization of LSF Parameters for Wideband Speech Codecs

  • Park, Jung-Eun;Kang, Sang-Won
    • ETRI Journal
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    • v.30 no.5
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    • pp.738-740
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    • 2008
  • In this paper, block constrained trellis coded vector quantization (BC-TCVQ) is presented for quantizing the line spectrum frequency parameters of the wideband speech codec. Both a predictive structure and a safety-net concept are combined into BC-TCVQ to develop the predictive BC-TCVQ. The performance of this quantization is compared with that of the linear predictive coding vector quantizer used in the AMRWB codec, demonstrating reductions in spectral distortion.

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Implementation of Communication Unit for KOMPSAT-II (다목적실용위성 2호기의 통신 부호화기 구현)

  • 이상택;이종태;이상규
    • Proceedings of the IEEK Conference
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    • 2003.11c
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    • pp.378-381
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    • 2003
  • The Channel Coding Unit (CCU) is an integral component of Payload Data Transmission System (PDTS) for the Multi-Spectral Camera (MSC) data. The main function of the CCU is channel coding and encryption. CCU has two channels (I & Q) for data processing. The input of CCU is the output of DCSU (Data Compression & Storage Unit). The output of CCU is the input of QTX which modulate data for RF communication. In this paper, there are the overview, short H/W description and operation concept of CCU.

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Voice Activity Detection Based on Entropy in Noisy Car Environment (차량 잡음 환경에서 엔트로피 기반의 음성 구간 검출)

  • Roh, Yong-Wan;Lee, Kue-Bum;Lee, Woo-Seok;Hong, Kwang-Seok
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.2
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    • pp.121-128
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    • 2008
  • Accurate voice activity detection have a great impact on performance of speech applications including speech recognition, speech coding, and speech communication. In this paper, we propose methods for voice activity detection that can adapt to various car noise situations during driving. Existing voice activity detection used various method such as time energy, frequency energy, zero crossing rate, and spectral entropy that have a weak point of rapid. decline performance in noisy environments. In this paper, the approach is based on existing spectral entropy for VAD that we propose voice activity detection method using MFB(Met-frequency filter banks) spectral entropy, gradient FFT(Fast Fourier Transform) spectral entropy. and gradient MFB spectral entropy. FFT multiplied by Mel-scale is MFB and Mel-scale is non linear scale when human sound perception reflects characteristic of speech. Proposed MFB spectral entropy method clearly improve the ability to discriminate between speech and non-speech for various in noisy car environments that achieves 93.21% accuracy as a result of experiments. Compared to the spectral entropy method, the proposed voice activity detection gives an average improvement in the correct detection rate of more than 3.2%.

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Statistical Error Compensation Techniques for Spectral Quantization

  • Choi, Seung-Ho;Kim, Hong-Kook
    • Speech Sciences
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    • v.11 no.4
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    • pp.17-28
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    • 2004
  • In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pairs (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods based on linear mapping functions according to different assumption of distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. We apply the proposed techniques to a predictive vector quantizer used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064dB.

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Enhanced Adjustment Strategy of Masking Threshold for Speech Signals in Low Bit-Rate Audio Coding (저전송률 오디오 부호화에서 음성 신호의 성능 개선을 위한 마스킹 임계값 적응기법 향상)

  • Lee, Chang-Heon;Kang, Hong-Goo
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.1
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    • pp.62-68
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    • 2010
  • This paper proposes a new masking threshold adjustment strategy to improve the performance for speech signals in low bit-rate audio coding. After determining formant regions, the masking threshold is adjusted by using the energy ratio of each sub-band to the average energy of each formant. More quantization noises are added to the bands that have relatively large energy, but less distortion is allowed in spectral valley regions by allocating more bits, which reflects the concept of perceptual weighting widely used in speech coding. From the results of objective speech quality measure, we verified that the proposed method improves quality for the speech input signals compared to the conventional one.

Enhanced Prediction Algorithm for Near-lossless Image Compression with Low Complexity and Low Latency

  • Son, Ji Deok;Song, Byung Cheol
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.2
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    • pp.143-151
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    • 2016
  • This paper presents new prediction methods to improve compression performance of the so-called near-lossless RGB-domain image coder, which is designed to effectively decrease the memory bandwidth of a system-on-chip (SoC) for image processing. First, variable block size (VBS)-based intra prediction is employed to eliminate spatial redundancy for the green (G) component of an input image on a pixel-line basis. Second, inter-color prediction (ICP) using spectral correlation is performed to predict the R and B components from the previously reconstructed G-component image. Experimental results show that the proposed algorithm improves coding efficiency by up to 30% compared with an existing algorithm for natural images, and improves coding efficiency with low computational cost by about 50% for computer graphics (CG) images.

Coding of remotely sensed satellite image data using region classification and interband correlation (영역 분류 및 대역간 상관성을 이용한 원격 센싱된 인공위성 화상데이타의 부호화)

  • 김영춘;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.8
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    • pp.1722-1732
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    • 1997
  • In this paper, we propose a coding method of remotely sensed satellite image data using region classification and interband correlation. This method classifies each pixel vector consider spectral characteristics. Then we perform the classified intraband VQ to remove spatial (intraband redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the band images that the high correlation spectrally and perform the classified interband VQ for the remaining band images. Experiments on LANDSAT TM image show that the coding efficiency of the proposed method is better than that of the conventional Gupta's method. Especially, this method removes redundancies effectively for satellite iamge including various geographical objects and for and images that have low interband correlation.

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Cross-Correlated Quadrature Amplitude Modulation for Non-Orthogonal Multiple Access in 5G Systems

  • Chung, Kyuhyuk
    • International Journal of Advanced Culture Technology
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    • v.9 no.3
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    • pp.283-290
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    • 2021
  • Recently, correlated superposition coding (CSC) has been proposed to implement non-orthogonal multiple access (NOMA) without successive interference cancellation (SIC), without loss of spectral efficiency, in contrast to conventional independent superposition coding (ISC). However, correlation between signals has reduced the average total allocated power, which results in degraded performance. Thus, in order to avoid the reduction of the average total allocated power owing to correlation between signals, this paper proposes a cross-correlated quadrature amplitude modulation (QAM) NOMA scheme under Rayleigh fading channel surroundings. First, we design the cross-correlated QAM NOMA scheme. Then, simulations demonstrate that for the weaker channel gain's user, the symbol error rate (SER) performance of the proposed cross-correlated QAM NOMA improves largely, whereas for the stronger channel gain's user, the SER performance of the proposed cross-correlated QAM CSM NOMA degrades little, compared to that of the conventional QAM NOMA.