• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.1
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• pp.75-85
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• 1985

We have studied on the 2-D moving target tracking algorithm satisfying a real-time hardware implementation requirement. In this paper, a fast algorithm is developed based on the operator formulation and the variational algorithm f 10] . Here, we use the directed search for the maximum of the cross-correlation in order to obtain an initial estimate for the variational algorithm and decompose the scene into 16 smaller subblocks and apply the variational algorithm to each subblock sequentially with a new moving area detection method. We call the algorithm subblock based recursive algorithm. Compared with (10) , the ratio of the computational savings obtained from the proposed algorithm is 7 on the average.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1199-1203
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• 2012

H.264 adopted many compression tools to increase image data compression efficiency such as B frame bi-directional predictions, the direct mode coding and so on. Despite its high compression efficiency, H.264 can suffer from its long coding time due to the complicated tools of H.264. To realize a high performance H.264, several fast algorithms were proposed. One of them is adaptive fast direct mode decision algorithm using mode and Lagrangian cost prediction for B frame in H.264/AVC (MLP) algorithm which can determine the direct coding mode for macroblocks without a complex mode decision process. However, in this algorithm, macroblocks not satisfying the conditions of the MLP algorithm are required to process the complex mode decision calculation, yet suffering a long coding time. To overcome the problem, this paper proposes a fast direct mode prediction algorithm. Simulation results show that the proposed algorithm can determine the direct mode coding without a complex mode decision process for 42% more macroblocks and, this algorithm can reduce coding time by up to 23%, compared with Jin's algorithm. This enables to encode B frames fast with a less quality degradation.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.208-211
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• 2004

Landmark matching is one of an important algorithm for navigation of satellite images. This paper proposes a fast landmark matching algorithm using a MGLI (Moving Guide-Line Image). For searching the matched point between the landmark chip and a part of image, correlation matrix is used generally, but the full-sized correlation matrix has a drawback requiring plenty of time for matching point calculation. MGLI includes thick lines for fast calculation of correlation matrix. In the MGLI, width of the thick lines should be determined by satellite position changes and navigation error range. For the fast landmark matching, the MGLI provides guided line for a landmark chip we want to match, so that the proposed method should reduce candidate areas for correlation matrix calculation. This paper will show how much time is reduced in the proposed fast landmark matching algorithm compared to general ones.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.45-48
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• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.79-81
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• 1987

In this paper we propose a fast adaptive least squares algorithm for linear phase FIR filters. The algorithm requires 10m multiplications per data point where m is the filter order. Both linear phase cases with constant phase delay and constant group delay are examined. Simulation results demonstrate that the proeposed algorithm is superior to the LMS gradient algorithm and the averaging scheme used for the modified fast Kalman algorithm.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.105-125
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• 2005

Motivated by the field experimental designs in agriculture, the theory of block designs has been applied to several areas such as statistics, combinatorics, communication networks, distributed systems, cryptography, etc. An explicit formula and its fast computational algorithm for a class of symmetric balanced incomplete block designs are presented. Based on the formula and the careful investigation of the modulus multiplication table, the algorithm is developed. The computational costs of the algorithm is superior to those of the conventional ones.

• ETRI Journal
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• v.33 no.3
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• pp.401-406
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• 2011

This paper presents a fast block-matching algorithm based on the normalized cross-correlation, where the elimination order is determined based on the gradient magnitudes of subblocks in the current macroblock. Multilevel Cauchy-Schwartz inequality is derived to skip unnecessary block-matching calculations in the proposed algorithm. Also, additional complexity reduction is achieved re-using the normalized cross correlation values for the spatially neighboring macroblock because the search areas of adjacent macroblocks are overlapped. Simulation results show that the proposed algorithm can improve the speed-up ratio up to about 3 times in comparison with the existing algorithm.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.13-19
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• 1998

The Median of a set of number is a number which partitions the given set. The specified numbers of a set partitions in one subset and in another subset. In Image Processing, The Sorting method of numbers of one subset equal to the previous Median Filtering. but The Sorting method of numbers of another subset not equal to in the other. In this paper, a fast two-dimentional Median Filtering Algorithm is proposed. The Algorithm designed in such a during the partitioning of the previous window are used. Test results obtained by running the Algorithm on IBM PC(586) are presented and its filtering. It is shown that the proposed Algorithm's processing time is faster and independent of the number of bits used to represent the data values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.658-675
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• 2022

This paper presents a fast-simplified successive cancellation (SC) flipping (Fast-SSC-Flip) decoding algorithm for polar code. Firstly, by researching the probability distribution of the number of error bits in a node caused by channel noise in simplified-SC (SSC) decoder, a measurement criterion of node reliability is proposed. Under the guidance of the criterion, the most unreliable nodes are firstly located, then the unreliable bits are selected for flipping, so as to realize Fast-SSC-Flip decoding algorithm based on node reliability (NR-Fast-SSC-Flip). Secondly, we extended the proposed NR-Fast-SSC-Flip to multiple node (NR-Fast-SSC-Flip-ω) by considering dynamic update to measure node reliability, where ω is the order of flip-nodes set. The extended algorithm can correct the error bits in multiple nodes, and get good performance at medium and high signal-to-noise (SNR) region. Simulation results show that the proposed NR-Fast-SSC-Flip decoder can obtain 0.27dB and 0.17dB gains, respectively, compared with the traditional Fast-SSC-Flip [14] and the newly proposed two-bit-flipping Fast-SSC (Fast-SSC-2Flip-E2) [18] under the same conditions. Compared with the newly proposed partitioned Fast-SSC-Flip (PA-Fast-SSC-Flip) (s=4) [18], the proposed NR-Fast-SSC-Flip-ω (ω=2) decoder can obtain about 0.21dB gain, and the FER performance exceeds the cyclic-redundancy-check (CRC) aided SC-list (CRC-SCL) decoder (L=4).

• Journal of Industrial Technology
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• v.24 no.B
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• pp.143-148
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• 2004

We present a fast algorithm for CDMA (code division multiple access) multiuser detection using the gradient guided search. The fast algorithm calculates the maximum likelihood (ML) metric so efficiently that it needs only O(K) additions in the presence of K users once some initialization is completed. The computational advantages of the fast algorithm over the conventional method are more noticeable as more iterations are required to obtain a suboptimal solution as in the initialization with matched filters.