• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.425-428
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• 2005

This paper is made up Advanced Image Coding(AIC) that combines algorithms from next generation image coding standard, H.264/MPEG-4 Part 10 advanced video coding(AVC) and still image compression standard, JPEG(Joint Photographic Experts Group). AIC combines intra frame block prediction from H.264 with a JPEG style discrete cosine transform and quantization, followed by Context-based Adaptive Binary Arithmetic Coding(CABAC) as used in H.264. In this paper, we analyzes the efficiency of the AIC algorithm and JPEG and JPEG-2000, and it presents of result.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.328-338
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• 2005

Technology for compressing low-bitrate multichannel audio coding is being standardized owing to the increasing need of consumer for multichannel audio contents. In this paper we propose the sound source location cue coding (SSLCC) for extremely compressing multichannel audio to be suitable at the narrow bandwidth transmission environment. To improve the compression capability of the conventional binaural cue coding(BCC), the SSLCC adopts the virtual source location information (VSLI) as a spatial cue parameter, a symmetric uniform quantizer, and Huffman coder. The objective and subjective assessment results show that the SSLCC provides lower bitrate and better audio quality than conventional BCC method.

• ETRI Journal
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• v.43 no.2
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• pp.313-323
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• 2021

The Joint Video Exploration Team (JVET) has studied future video coding (FVC) technologies with a potential compression capacity that significantly exceeds that of the high-efficiency video coding (HEVC) standard. The joint exploration test model (JEM), a common platform for the exploration of FVC technologies in the JVET, employs quadtree plus binary tree block partitioning, which enhances the flexibility of coding unit partitioning. Despite significant improvement in coding efficiency for chrominance achieved by separating luminance and chrominance tree structures in I slices, this approach has intrinsic drawbacks that result in the redundancy of block partitioning data. In this paper, an adaptive tree structure correlating luminance and chrominance of single and dual trees is presented. Our proposed method resulted in an average reduction of -0.24% in the Y Bjontegaard Delta rate relative to the intracoding of JEM 6.0 common test conditions.

• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.13-18
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• 1998

The practical use of the particle image velocimetry(PIV), a whole-field velocity measurement method, requires the use of fast, reliable, computer-based methods for tracking velocity vectors. The full search block matching, the most widely studied and applied technique both in area of PIV and Image Coding and Compression, is computationally costly. Many less expensive alternatives have been proposed mostly in the area of Image Coding and Compression. Among others, TSS, NTSS, HPM are introduced for the past PIV analysis, and found to be successful. But, these algorithms are based on small dynamic range, 7 pixels/frame in maximum displacement. To analyze the images with large displacement, Even and Odd field image separation and a simple version of multi-resolution hierarchical procedures are introduced in this paper. Comparison with other algorithms are summarized. A Results of application to the turbulent backward step flow shows the improvement of new algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2326-2345
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• 2016

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1567-1570
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• 2002

This paper deals with FPGA(Field Programmable Gate Array) implementation of the AAC(Advanced Audio Coding) decoder. On modern computer culture, according to the high quality data is required in multimedia systems area such as CD, DAT(Digital Audio Tape) and modem. So, the technology of data compression far data transmission is necessity now. MPEG(Moving Picture Experts Group) would be a standard of those technology. MPEG-2 AAC is the availableness and ITU-R advanced coding scheme far high quality audio coding. This MPEG-2 AAC audio standard allows ITU-R 'indistinguishable' quality according to at data rates of 320 Kbit/sec for five full-bandwidth channel audio signals. The compression ratio is around a factor of 1.4 better compared to MPEG Layer-III, it gets the same quality at 70％ of the titrate. In this paper, for a real time processing MPEG2 AAC decoding, it is implemented on FPGA chip. The architecture designed is composed of general DSP(Digital Signal Processor). And the Processor designed is coded using VHDL language. The verification is operated with the simulator of C language programmed and ECAD tool.

• ETRI Journal
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• v.32 no.6
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• pp.972-975
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• 2010

In this letter, we consider the lossy coding of a non-uniform binary source based on GF(q)-quantized low-density generator matrix (LDGM) codes with check degree $d_c$=2. By quantizing the GF(q) LDGM codeword, a non-uniform binary codeword can be obtained, which is suitable for direct quantization of the non-uniform binary source. Encoding is performed by reinforced belief propagation, a variant of belief propagation. Simulation results show that the performance of our method is quite close to the theoretic rate-distortion bounds. For example, when the GF(16)-LDGM code with a rate of 0.4 and block-length of 1,500 is used to compress the non-uniform binary source with probability of 1 being 0.23, the distortion is 0.091, which is very close to the optimal theoretical value of 0.074.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.68-71
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• 1985

In this paper, Sentence-Sip E Il Ka Gi Seo U1 E Gan Da was spoken by 4 men and 3 see sound is used for the experiment. A/D conversion time is 30 sec. Data are obtained using the microcomputer and compressed by ADPCM Rate of compression is 1/8. Data compressed by ADPCM are synthesized and compared to the original sound. Rate of speech identification is analysed using the sound pressure, white noise. Coding of ADPCM is done for 5bit. As the result of fixing starting voltage by 2.6V. It is acertained that variable value increases in initial speech signal and then process is made by minimum value "3". From the result of processing, synthesized sound is almost eaual to original sound. Minimum values cause distorition, Dummy Head System is used in this experiment.xperiment.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.249-254
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• 2002

We consider a buffer-constrained adaptive quantization algorithm for image compression. Buffer control algorithm was considered with source coding scheme by some researchers and recently a formal description of the algorithm in terms of rate-distortion has been developed. We propose a buffer control algorithm that incorporates the buffer occupancy into the Lagrange multiplier form in a rate-distortion cost measure. Although the proposed algorithm provides the suboptimal performance as opposed to the optimal Vieterbi algorithm, it can be implemented with very low computaional complexity. In addition stability of this buffer control algorithm has been mentioned briefly using Liapnov stability theory.