• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.265-274
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• 1999

In this paper, we propose a novel interframe coding algorithm especially appropriate for 3-D medical images. The proposed algorithm is based on a video coding algorithm using motion estimation/ compensation and transform coding. In the algorithm, warping is adopted lor motion compensation (MC). Then, by using adaptive mode selection, a motion compensated residual image and original image are mixed up in the wavelet transform domain for improvement in coding performance. The mixed image is then compressed by the zerotree coding method. We prove that the adaptive mode selection technique in the wavelet transform domain is very useful lor 3-D medical image coding. Simulation results show that the proposed scheme provides good performance regardless of inter-slice distance and is prospective for 3-D medical image compression.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.195-197
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• 2005

In the scalable extension of H.264/AVC, spatial scalability is provided residual information as encoding layered spatial resolution between layers. We use the inter-layer prediction to remove this redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be different from optimal prediction by kinds of interpolation filter. This paper indicates technique to choose the interpolation filter and to enhance coding efficiency for finding more correct prediction in intra macroblock.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3672-3684
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• 2015

Recently, the standardization of backward compatible JPEG image coding for high dynamic range (HDR) image has been undertaken to establish an international standard called "JPEG XT." The JPEG XT consists of two layers: the base layer and the residual layer. The base layer contains tone mapped low dynamic range (LDR) image data and the residual layer contains the error signal used to reconstruct the HDR image. This paper gives the result of a study to evaluate the overall performance of tone mapping operators (TMOs) for this standard. The evaluation is performed using five HDR image datasets and six TMOs for profiles A, B, and C of the proposed JPEG XT standard. The Tone Mapped image Quality Index (TMQI) and no reference image quality assessment (NR IQA) are used for measuring the LDR image quality. The peak signal to noise ratio (PSNR) is used to evaluate the overall compression performance of JPEG XT profiles A, B, and C. In TMQI and NR IQA measurements, TMOs using display adaptive tone mapping and adaptive logarithmic mapping each gave good results. A TMO using adaptive logarithmic mapping gave good PSNRs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3841-3861
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• 2017

Virtualized small cell network is a promising architecture which can realize efficient utilization of the network resource. However, conventional full duplex self-backhauls lead to residual self-interference, which limits the network performance. To handle this issue, this paper proposes a virtual resource allocation, in which the residual self-interference is fully exploited by employing a physical-layer network coding (PNC) aided self-backhaul scheme. We formulate the features of PNC as time slot and information rate constraints, and based on that, the virtual resource allocation is formulated as a mixed combinatorial optimization problem. To solve the problem efficiently, it is decomposed into two sub problems, and a two-phase iteration algorithm is developed accordingly. In the algorithm, the first sub problem is approximated and transferred into a convex problem by utilizing the upper bound of the PNC rate constraint. On the basis of that, the convexity of the second sub problem is also proved. Simulation results show the advantages of the proposed scheme over conventional solution in both the profits of self-backhauls and utility of the network resource.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.731-739
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• 2017

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low complexity video sampling. In DCVS schemes, motion estimation & motion compensation is employed at the decoder side, similarly to distributed video coding (DVC), for a low-complex encoder. However, since a simple BCS-SPL algorithm is applied to a residual arising from motion estimation and compensation in conventional MC-BCS-SPL (motion compensated block compressed sensing with smoothed projected Landweber) scheme, the reconstructed visual qualities are severly degraded in Wyner-Ziv (WZ) frames. Furthermore, the scheme takes lots of iteration to reconstruct WZ frames. In this paper, the conventional MC-BCS-SPL algorithm is improved to be operated in more effective way in WZ frames. That is, first, the proposed algorithm calculates a correlation coefficient between two reference key frames and, then, by selecting adaptively the reference frame, the residual reconstruction in pixel domain is performed to the conventional BCS-SPL scheme. Experimental results show that the proposed algorithm achieves significantly better visual qualities than conventional MC-BCS-SPL algorithm, while resulting in the significant reduction of the decoding time.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1915-1919
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• 2003

A practical method of adaptive rate allocation to source and channel codings for an independent loss channel is proposed for Internet video. It is based on the observations that the values of residual loss probabilities at the optimal code rates for different packet loss probabilities are closely clustered to the average residual loss probability for a transmission frame size n in RS(n,k) code and for a total bit rate R. These observations aye then exploited to find the code rate for maximum PSNR. Simulation results demonstrate that the proposed method achieves a near-optimal bit-rate allocation in the joint source-channel coding of H.263 and RS(n,k) codings.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.377-380
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• 2007

In this paper, an improved CABAC is proposed for the lossless compression in H.264/AVC. CABAC in the lossless coding is not as efficient as that in the lossy compression since it was developed for lossy coding. CABAC for the lossless coding in H.26과/AVC Advanced 4:4:4 Profile is applied without the change of the conventional binarization method. Thus, a binarization method considering the statistical characteristic of residual signals is proposed for the lossless coding in 0.264/AVC Advanced 4:4:4 Profile. The experimental results show that the proposed method obtains approximately 3.4% bitrate reduction in comparison to that of the conventional lossless coding.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.163-166
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• 2000

In this paper, we will present a lossy data compression method for coding multispectral images. The proposed method uses both spatial and spectra] correlation inherent in multispectral images. First, band 2 and band 6 are vector quantized. Secondly, band 4 is estimated with the quantized band 2 using the predictive coding. Errors of band 4 are encoded at a second stage based on the magnitude of the errors. Thirdly, remaining bands are calculated with the quantized band 2 and band 4. Errors of residual bands are wavelet transformed and then we apply the SPIHT coding on the transformed coefficients. We classify classes without extra information transmitting and then use linear predictor. And errors can be encoded by SPIHT coding at any target rate we are want. It is shown that this method has better performance than FPVQ. Average PSNR rises 0.645 dB at the same bit rate.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.549-556
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• 2008

To achieve flexible visual content adaption for multimedia communications, the ISO/IEC MPEG & ITU-T VCEG form the JVT to develop SVC amendment for the H.264/AVC standard. JVT uses inter-layer prediction as well as inter prediction and intra prediction that are provided in H.264/AVC to remove the redundancy among layers. The main goal consists of designing inter-layer prediction tools that enable the usage of as much as possible base layer information to improve the rate-distortion efficiency of the enhancement layer. But inter layer prediction causes the computational complexity to be increased. In this paper, we proposed an efficient residual prediction. In order to reduce the computational complexity while maintaining the high coding efficiency. The proposed residual prediction uses modified interpolation that is defined in H.264/AVC SVC.