• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.393-393
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• 2006

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.16-16
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• 2003

Purpose： Recently, a major interesting method of fast MR imaging is sensitivity encoding (SENSE) using arrays of multiple receiver coils. In this study, we have designed and implemented a 4-channel head array coil and optimized the structure and arrangement of the coil to improve the performance.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.519-528
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• 2016

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.124-131
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• 1997

There have been many demands for th ereal-time image compression. The image compression systems have a wide range of applications. However, real-time encoding is hard to implement because it needs a large amount of computations. In particular, the discrete cosine transform (DCT) and motion estimatio require a large number of arithmetic oeprations compared to other algorithms in MPEG-2. The conventional fasdt DCT algorithms have focused on the reduction of the number of additions more cycles and more expense in realization. Because TMS320C80 has special structure, new approach for implementation of DCT is suggested. The selection of adaptive algorithm and optimization is requried TMS320C80 are analyzed an dsome adaptive DCT algorithms are selected. The DCT algorithms are optimized and implemented. Chens and lees DCT algorithms among various fast algorithms are selected because 1-D approach is effective in the view of th einternal structure of TMS320C80. According to the simulation result, Lees algorithm is more effective in speed and has little difference in precision. On the basis of the result, the possibility of DCT implementation for real-time MPEG-2 system is verified and the required number of the processor, called advanced DSP, is decided for real-time MPEG-2 encoding and decoding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.779-787
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• 2003

In this paper, we propose an improved early detection of all-zero DCT coefficients for fast video encoding. From the experimental observation, it is shown that the performance of the conventional method is limited because of the imprecision sufficient condition. When the calculation of the SAD in motion estimation is simply modified, more precise sufficient condition is derived from the theoretical analysis. Based on this idea, DCT and the quantization stages are effectively skipped in the proposed algorithm with no image degradation. The simulation results show that the proposed algorithm achieves computational saving over 10% compared to the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2355-2364
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• 1998

In conventional fractal decoding procedure, the reconstructed image is obtained by a rpredefined number of iterations starting with an arbitrary initial image. Its convergence speed depends on the selection of the initial image. It should be solved to get high speed convergence. In this paper, we theoretically reveal that conventional method is approximately decomposed into the decoding of the DC and AC components. Based on this fact, we proposed a novel fast fractal decoding algorithm made up of two steps. The averaged-image considered as an optimal initial image is estimated in the first step. In the second step, the reconstructe dimag eis genrated from the output image obtained in the first step. From the simulations, it is shown that the output image of the first step approximately converges to the averaged-image with only 15% calculations for one iteration of conventional method. And the proposed method is faster than various decoding mehtods and evenly equal to conventioanl decoding with the averaged-image. In addition, the proposed method can be applied to the compressed data resulted from the various encoding methods because it does not impose any constraints in the encoding procedure to get high decoding speed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.34-44
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• 2008

In this paper, a new rate-distortion estimation method is proposed for fast rate-distortion optimized(RDO) mode decision in H.264 encoder. A bit-rate and distortion should be calculated by encoding and reconstruction of each macroblock mode in order to select the optimal RDO mode. To reduce the computations for getting them, a bit-rate and distortion is efficiently estimated in DCT domain. Simulation results show that the proposed method achieves computational saving about 81% of RDO mode decision and saves about 26% of total encoding time without noticeable degradation in coding performance.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.152-161
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• 2008

We investigate that when we restrict the encoding modes on the enhancement layer based on that of the base layer exploiting the high correlation between the best modes at base and enhancement layers, we should determine the set of surviving search modes to yield the minimum excessive RD-cost caused by the restriction. Based on these sets, we implement a fast mode decision algorithm for H.264 Scalable Extension (SE). Simulation results show that the proposed algorithm is superior in the sense of the RD-performance to the conventional mode restriction method which is based on the conditional probabilities of the best modes.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.2 s.332
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• pp.83-88
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• 2005

We propose the design method for the VLSI architecture of FNNPDS combined PDS(partial distance search) and FNNS(fast nearest neighbor search), which are used to fast encoding in vector quantization, and obtain the results that FNNPDS(fast nearest neighbor partial distance search) is faster method than the conventional methods by simulation. In simulations, we investigate timing diagrams described searching time of the nearest codevector for an input vector, and compare the average clock cycles per input vector for Lena and Peppers images. According to the result of simulations, the number of the clock cycle of FNNPDS was reduced to $79.2\%\~11.7\%$ as compared with the number using the conventional techniques.