• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.838-841
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• 2009

This paper proposes a novel lossless coding scheme for Bayer color filter array (CFA) images which are generally used as internal data of color digital cameras having a single image sensor. The scheme employs a block-adaptive prediction method to exploit spatial and spectral correlations in local areas containing different color signals. In order to allow adaptive prediction suitable for the respective color signals, four kinds of linear predictors which correspond to 2 ${\times}$ 2 samples of Bayer CFA are simultaneously switched block-by-block. Experimental results show that the proposed scheme outperforms other state-of-the-art lossless coding schemes in terms of coding efficiency for Bayer CFA images.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.706-712
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• 2006

Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1614-1623
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• 1995

In this paper we propose a region-adaptive CELP image coder for still images at low bit rates below 0.5 bpp. The proposed method partitions the image into stochastically similar regions by the minimum spanning tree method and finds prediction coefficients for each region using a 2- dimensional linear prediction model. Coding is carried out on 8$\times$8 blocks and when there are several regions included in a block, an image is synthesized using the prediction coefficients of each region. Computer simulation results show that the proposed method allows improved synthesized image over conventional block-adaptive CELP methods, especially at edges. In addition, performance comparison with the JPEG DCT method shows that while the JPEG method shows block distortion and staircase effects (ragged edges) at bit rates below 0.5 bpp, the proposed CELP method shows improved synthesized images with such effects reduced.

• ETRI Journal
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• v.34 no.1
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• pp.106-109
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• 2012

In this letter, we propose a new prediction block filter that can reduce errors between the original and prediction blocks. The proposed filter adaptively adjusts filter coefficients by using the previously reconstructed adjacent blocks and their prediction blocks. Then, the filter is selectively applied to the current prediction block according to the rate-distortion optimization. Moreover, since the same filter coefficients can be derived in the decoder, they are not encoded into the bit-stream. The proposed method achieves a 4.65% bitrate saving on average compared with H.264/AVC.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.793-794
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• 2008

The block size of intra prediction mode can differentiate the texture area from the homogeneous area of image. This information can be used to enhance the size resolution of image. Specifically, in this paper, we apply the bicubic interpolation or the bilinear interpolation adaptively selected the intra prediction mode of the H.264 compression.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.199-204
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• 1994

In this paper, we researched abut CELP speech coding algorithm using efficlent pseudo-stochastic block codes, adaptive-codebook and improved fixed-gain codebook. The pseudo-stochastic block codes refer to stochastically populated block codes in which the adjacent codewords in an innovation codebook are non-independent. The adaptive-codebook was made with previous prediction speech data by storage-shift register. This CELP coding algorithm enables the coding of toll quality speech at bit rates from 4.8kbits/s to 9.6 kbits/s. This algorithm was realized TMS320C30 microprocessor in realtime.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.813-820
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• 2018

This paper proposes new frame rate up-conversion algorithms. Adaptive motion estimation based on block complexity information are used to obtain more accurate motion vectors. Because the information on block complexity is extracted from the motion estimation prediction size from the original frame, additional computational complexity is not imparted. In experimental results, the proposed algorithms provide robust frame interpolation performance for whole test sequences. Also, the computational complexity of the proposed algorithm is reduced to a benchmark algorithm.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.39-42
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• 2005

H.264, a recently proposed international video coding standard, has adopted context-based adaptive variable length coding (CAVLC) as the entropy coding tool in the baseline profile. By combining an adaptive variable length coding technique with context modeling, we can achieve a high degree of redundancy reduction. However, CAVLC in H.264 has weakness that the correct prediction rate of the variable length coding (VLC) table is low in a complex area, such as the boundary of an object. In this paper, we propose a VLC table prediction scheme considering multiple reference blocks; the same position block of the previous frame and the neighboring blocks of the current frame. The proposed algorithm obtains the new weighting values considering correctness of the VLC table for each reference block. Using this method, we can enhance the prediction rate of the VLC table and reduce the bit-rate.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.332-340
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• 2022

Recently, with the development of deep learning and artificial neural network technologies, research on the application of neural network has been actively conducted in the field of video coding. In particular, deep learning-based intra prediction is being studied as a way to overcome the performance limitations of the existing intra prediction techniques. This paper presents a method of context-adaptive neural network-based intra prediction model training and its coding performance analysis. In other words, in this paper, we implement and train a known intra prediction model based on convolutional neural network (CNN) that predicts a current block using contextual information from reference blocks. Then, we integrate the trained model into HM16.19 as an additional intra prediction mode and evaluate the coding performance of the trained model. Experimental results show that the trained model gives 0.28% BD-rate bit saving over HEVC in All Intra (AI) coding mode. In addition, the coding performance change of training considering block partition is also presented.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.785-790
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• 2019

In this paper, a new bilateral frame rate up-conversion algorithm using adaptive overlapped block motion compensation is proposed. In this algorithm, the adaptive overlapped block motion compensation is based on the motion complexity of the reference region. As the motion complexity is determined by the size of the previously coded motion estimation prediction, the overlapped block motion compensation method is selected without any additional computational complexity. Experimental results show that the proposed algorithm provides better image quality than conventional methods both objectively and subjectively.