• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.12
• /
• pp.2725-2730
• /
• 2012

In this paper, for improving the H.264/AVC hardware performance, we propose an inter predictor hardware design using a multi reference frame selector and an implicit weighted predictor. previous reference frame are reused for Low Memory Bandwidth. The size of the reference memory in the predictor was reduced by about 46% and the external memory access rate was reduced by about 24% compared with the one in the reference software JM16.0. We designed the proposed system with Verilog-HDL and synthesized inter predictor circuit using the Magnachip 0.18um CMOS standard cell library. The synthesis result shows that the gate count is about 2,061k and the design can run at 91MHz.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.5
• /
• pp.435-441
• /
• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.4
• /
• pp.736-739
• /
• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3295-3311
• /
• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Journal of information and communication convergence engineering
• /
• v.11 no.2
• /
• pp.118-123
• /
• 2013

This paper proposes an efficient hardware architecture for high efficiency video coding (HEVC), which is the next generation video compression standard. It adopts several new coding techniques to reduce the bit rate by about 50% compared with the previous one. Unlike the previous H.264/AVC 6-tap interpolation filter, in HEVC, a one-dimensional seven-tap and eight-tap filter is adopted for luma interpolation, but it also increases the complexity and gate area in hardware implementation. In this paper, we propose a parallel architecture to boost the interpolation performance, achieving a luma $4{\times}4$ block interpolation in 2-4 cycles. The proposed architecture contains shared operations reducing the gate count increased due to the parallel architecture. This makes the area efficiency better than the previous design, in the best case, with the performance improved by about 75.15%. It is synthesized with the MagnaChip $0.18{\mu}m$ library and can reach the maximum frequency of 200 MHz.

• Journal of Electrical Engineering and Technology
• /
• v.2 no.3
• /
• pp.335-341
• /
• 2007

In this study, we present an approach to parallelizing OPF that is suitable for distributed implementation and is applicable to very large inter-connected power systems. The approach could be used by utilities for optimal economy interchange without disclosing details of their operating costs to competitors. It could also be used to solve several other computational tasks, such as state estimation and power flow, in a distributed manner. The proposed algorithm was demonstrated with several case study systems.

• Journal of Broadcast Engineering
• /
• v.24 no.3
• /
• pp.401-410
• /
• 2019

In this paper, we propose a reference picture generation method for Inter-layer prediction based deep learning to improve the SHVC coding performance. A description will be given of a structure for performing filtering using a VDSR network on a DCT-IF based upsampled picture to generate a new reference picture and a training method for generating a reference picture between SHVC Inter-layer. The proposed method is implemented based on SHM 12.0. In order to evaluate the performance, we compare the method of generating Inter-layer predictor by applying dictionary learning. As a result, the coding performance of the enhancement layer showed a bitrate reduction of up to 13.14% compared to the method using dictionary learning, a bitrate reduction of up to 15.39% compared to SHM, and a bitrate reduction of 6.46% on average.

• Journal of Families and Better Life
• /
• v.22 no.3
• /
• pp.47-61
• /
• 2004

The major purpose of the present research was to examine the effect of adolescents's perception of parents' marital relationship and attachment with their parents on school adjustment. This study also tried to investigate the inter-relationship among related variables, and the differences in the level of school adjustment according to adolescents' general characteristics. The participants were 355 middle and high school students who lived in Chollabuk-Do province. The major results of this research were as follows. First, there were significant differences in the level of school adjustment according to sex, age, and grade point. average That is, the level of school adjustment was higher for males, for older adolescents, and for those recording higher grade point, than for females, for younger, and for those recording relatively lower grade point. Second, parents' marital relationship was positively correlated with positive aspects of attachment with their parents(i.e., communication and trust), and with school adjustment. but negatively correlated with negative aspect of attachment(i.e., alienation from their parents). Finally, multiple regression analyses were performed to analyze the relative significance of the related variables influencing on school adjustment after controlling the effect of sex, age, and grade point. It was found that communication with fathers was the most powerful predictor of school adjustment, while attachment with mothers was not found to be a significant predictor of school adjustment.

• Journal of Broadcast Engineering
• /
• v.19 no.2
• /
• pp.227-239
• /
• 2014

This paper proposes an enhance prediction for conventional near-lossless coder to effectively lower external memory bandwidth in image processing SoC. First, we utilize an already reconstructed green component as a base of predictor of the other color component because high correlation between RGB color components usually exists. Next, we can improve prediction performance by applying variable block size prediction. Lastly, we use minimum internal memory and improve a temporal prediction performance by using a template dictionary that is sampled in previous frame. Experimental results show that the proposed algorithm shows better performance than the previous works. Natural images have approximately 30% improvement in coding efficiency and CG images have 60% improvement on average.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.156-161
• /
• 2003

It is an interest problem to predict substance distributions in three-dimensional space. Recently, a research field as Geostatistics is advanced. It is a kind of inter- or extrapolation mathematically. Some useful means for the inter- and extrapolation are known, in which slide window method with neural networks is hopeful one. We propose multi-dimensional extrapolation using multi-layer neural networks and the slide-window method. The multi-dimensional extrapolation is not similar to one-dimension. It has plural algorithms. We researched line predictors and local-plain predictors I two-dimensional space. The both predictors are equivalent; however, in multi-dimensional extrapolation, it is very important to find the direction of predictions. Especially, since the slide window method requires information to predict the future in sampling data, if they are not ordered appropriately in the direction, the predictor cannot operate. We tested the extrapolation for typical two-dimensional functions, and found an excellent character of slide-window method based on local-plain. By using the method, we can extrapolate the function until twice-outer regions of the definitions.