• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.1C
• /
• pp.69-77
• /
• 2002

Sine digital signal processing for motion pictures requires huge amount of data computation to store, manipulate and transmit, more effective data compression is necessary. Therefore, the ITU-T recommended H.26x as data compression standards for digital motion pictures. The data compression method that eliminates time redundancies by motion estimation using relationship between picture frames has been widely used. Most video conding systems employ block matching algorithm for the motion estimation and compensation, and the algorithm is based on the minimun value of cast functions. Therefore, fast search algorithm rather than full search algorithm is more effective in real time low data rates encodings such as H.26x. In this paper, motion estimation employing the Nearest-Neighbors algorithm is designed to reduce search time using FPGA, coded in VHDL, and simulated and verified using Xilink Foundation.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.2
• /
• pp.20-28
• /
• 2003

Recently we need a faster and more accurate motion vector search algorithm for ASIC(Application Specific IC) or small systems. Block motion estimation using Full Search(FS) algorithm provides the best visual quality and PSNR, but it requires intensive computations. The previously proposed fast algorithms reduced the number of computations by limiting the number of searching locations. This is accomplished at the expense of less accuracy of motion estimation and gives rise to an appreciably higher SAD(Sum of Absolute Difference) for motion compensated images. In this paper we exploit the spatial correlation of motion vectors and present a fast motion estimation scheme which uses the predicted motion vector(PMV). The PMV scheme is more clear and simpler than the previously proposed algorithms which also use adjacent motion vectors. Simulation results with standard video sequences show that the PMV scheme is faster and more accurate than other algorithms such as Nearest-Neighbors Search(NNS) algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.7B
• /
• pp.647-659
• /
• 2003

LPM(Longest Prefix Matching)searching in If address lookup is a major bottleneck of IP packet processing in the high speed router. In the conventional lookup table for the LPM searching in CAM(Content Addressable Memory) the complexity of fast update take 0(1). In this paper, we designed pipeline architecture for fast update of 0(1) cycle of lookup table and high throughput and low area complexity on LPM searching. Lookup-table architecture was designed by CAM(Content Addressable Memory)away that uses 1bit RAM(Random Access Memory)cell. It has three pipeline stages. Its LPM searching rate is affected by both the number of key field blocks in stage 1 and stage 2, and distribution of matching Point. The RTL(Register Transistor Level) design is carried out using Verilog-HDL. The functional verification is thoroughly done at the gate level using 0.35${\mu}{\textrm}{m}$ CMOS SEC standard cell library.

• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.305-315
• /
• 2008

Pre-proposed AHHS(Adaptive Hierarchical Hexagon Search) is a kind of the fast hierarchical block matching algorithm based on the AHS(Adaptive Hexagon Search). It is characterized as keeping the merits of the AHS capable of fast estimating motion vectors and also adaptively reducing the local minima often occurred in the video sequences with higher spatio-temporal motion activity. The objective of this paper is to propose the method effectively extending the horizontal biased pattern and the vertical biased pattern of the AHHS to improve its predictive image quality. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive image quality and the computational time. The simulation results indicated that the proposed method was both suitable for (quasi-) stationary and large motion searches. While the proposed method increased the computational load on the process extending the hexagon search patterns, it could improve the predictive image quality so as to cancel out the increase of the computational load.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.2
• /
• pp.21-27
• /
• 2000

In Fast motion estimaion algorithms, they reduce the computational complexity using the assumption that the matching error increases monotonically as the search moves away from the global minimum error In this paper, we first investigate the statistical characteristics of motion vector that the motion vector mostly occures on the side of small MAE (mean absolute error) between the reference search points when the MAE difference of them is large Therefore, we propose a fast motion estimation algorithm using this property and can reduce the number of search points The computer simulation result shows that the proposed method reduces computational complexity compared with conventional fast algorithms.

• Journal of KIISE:Computing Practices and Letters
• /
• v.10 no.1
• /
• pp.57-65
• /
• 2004

In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the unit-diamond search pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the unit-diamond search pattern, and then fastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed unit-diamond and flat-hexagonal pattern search algorithm(UDFHS) improves as high as 11∼51% in terms of average number of search point per motion vector estimation and improves about 0.05∼0.74㏈ in terms of PSNR(Peak Signal to Noise Ratio).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9A
• /
• pp.1401-1410
• /
• 1999

In this paper, we propose a fast block matching algorithm using the lower and upper bound of mean absolute difference (MAD) which is calculated at the search region overlapped with neighbor blocks. At first, we calculate the lower bound of MAD and reduce the search point by using this lower bound. In this method, we can get good prediction error performance close to full search block matching algorithm (FSBMA), but there exists some computational complexity that has to be reduced. Therefore, we further reduce the computational complexity by using pixel subsampling besides the lower and upper bound of MAD. Experimental results show that we can remarkably reduce the computational complexity with good prediction error performance close to FSBMA.

• Journal of Broadcast Engineering
• /
• v.5 no.2
• /
• pp.247-259
• /
• 2000

This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.1
• /
• pp.43-49
• /
• 2001

EVRC (Enhanced Variable Rate Codec) has been adopted as a standard coder for the CDMA digital cellular system in North America and Korea, and known to provide good call quality at 8kbps. In this paper, fast implementation algorithms for EVRC encoder are proposed. The proposed algorithms are based on both efficient pitch detection scheme and fast fixed codebook search algorithm. In the codebook search, computational complexity is reduced down to 70％ of the original EVRC by limiting the number of pulse position combination and by using a truncated impulse response. The proposed algorithms enable us to implement the EVRC with much smaller computational works. Also, informal subjective tests confirmed that the difference in the speech quality between the original EVRC and the proposed method was indistinguishable.

• Korean Journal of Optics and Photonics
• /
• v.19 no.1
• /
• pp.1-8
• /
• 2008

Shack-Hartmann sensors are widely employed as a wavefront measuring device in various applications. Adaptive optics is one of the major applications. Since an adaptive optics system should be operated in real-time, high-speed wavefront sensing is essential. In high-speed operation, integration time of an image detector is very short. In this case, noises such as readout noise and photon noise greatly influence the accuracy of wavefront sensing. Therefore a fast and noise-insensitive centroid finding algorithm is required for the real-time wavefront sensing. In this paper, the multi-resolution correlation method is proposed. By employing multi-resolution images, this method greatly reduces the computation time when compared to the fast Fourier transform (FFT) correlation method. The verification is performed through the computational simulation. In this paper, the center of mass method, correlation method and multi-resolution correlation method are employed to compare the measurement accuracy of the centroid finding algorithms. The accuracy of a Shack-Hartmann wavefront sensor using the proposed algorithm is proved to be comparable to that of the conventional correlation method.