• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.55-63
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• 2010

In this paper, a new video watermarking algorithm using 3D wavelet transform and position encoding of spread spectrum correlation is proposed as a method for ensuring enough payload in order to protect copyright for video contents. This algorithm provides better robustness than other watermarking methods in bit error and rotation because it uses the position encoding and $4{\times}4$ sample space instead of $1{\times}1$ pixel to express a digit. The evaluation result over 6 video clips shows that the PSNR is over 31dB at strength 11 when histogram is narrow and it satisfies the transparency. Also, it shows the robustness of the proposed watermark algorithm that the BER is 0% to three codecs.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.544-554
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• 2012

Screen content refers to images or videos generated by various electronic devices such as computers or mobile phones, whereas natural content refers to images captured by cameras. Screen contents show different statistical characteristics from natural images, so the conventional video codecs which were developed mainly for the coding of natural videos cannot guarantee good coding performances for screen contents. Recently, researches on efficient SCC(Screen Content Coding) are being actively studied, and especially at ongoing JCT-VC(Joint Collaborative Team on Video Coding) meeting for HEVC(High Efficiency Video Coding) standard, SCC issues are being discussed steadily. In this paper, we analyze the performances of high efficient coding tools in HM(HEVC Test Model) on SCC, and present an optimized SCC model based on the analysis results. We also present the characteristics of screen contents and the future research issues as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.505-513
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• 2004

Most video codecs including the international standards use the block-based hybrid structure for efficient compression. But for low bit-rate applications such as video transmission through wireless channels, the blocking artifacts degrade image qualify seriously. In this paper, we propose an adaptive de-blocking algorithm using characteristics of the block boundaries. Blocking artifacts contain the high frequency components near the block boundaries, therefore the lowpass filtering can remove them. However, simple lowpass filtering results into blurring by removing important information such as edges. To overcome this problem, we determine the modes depending upon the characteristics of pixels adjacent to block boundary then proper filter is applied to each area. Simulation results show that proposed method improves de-blocking performance compared to that of MPEG-4.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.95-105
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• 2005

This paper proposes a new dynamic video adaptation scheme that could generate an adapted video stream customized to the requesting mobile device and current network status without repeated decode-encode cycles. In the proposed adaptation scheme, the characteristics of the video codec such as MPEG-1/-2/-4 are analyzed in advance focused on the relationships between the size and Quality of the encoded video stream, and they are stored in the proxy as a codec-dependent characteristic table. When a mobile device requests a video stream, it is dynamically decoded-encoded in the proxy with the highest quality to extract the contents-dependent attributes of the requested video stream. By comparing these attributes with codec-dependent characteristic table, the size and Quality of the requested video stream when being adapted to the target mobile device could be predicted. With this prediction, a version of adapted video stream, that meets the size constraints of mobile device while keeping the quality of encoded video stream as high as possible, could be selected without repeated decode-encode cycles. Experimental results show that the errors in our proposed scheme are less than 5% and produce an appropriate adapted video stream very quickly. It could be used t(1 build a proxy server for mobile devices that could quickly transcode the video streams widely spread in Internet which are encoded with various video codecs.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.42-54
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• 2023

It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.446-457
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• 2017

In order to reduce the size of frame memory or bus bandwidth, frame memory compression (FMC) recompresses reconstructed or reference frames of video codecs. This paper proposes a novel FMC design based on discrete wavelet transform (DWT) - set partitioning in hierarchical trees (SPIHT), which supports fine-scalable throughput and is area-efficient. In the proposed design, multi-cores with small block sizes are used in parallel instead of a single core with a large block size. In addition, an appropriate pipelining schedule is proposed. Compared to the previous design, the proposed design achieves the processing speed which is closer to the target system speed, and therefore it is more efficient in hardware utilization. In addition, a scheme in which two passes of SPIHT are merged into one pass called merged refinement pass (MRP) is proposed. As the number of shifters decreases and the bit-width of remained shifters is reduced, the size of SPIHT hardware significantly decreases. The proposed FMC encoder and decoder designs achieve the throughputs of 4,448 and 4,000 Mpixels/s, respectively, and their gate counts are 76.5K and 107.8K. When the proposed design is applied to high efficiency video codec (HEVC), it achieves 1.96% lower average BDBR and 0.05 dB higher average BDPSNR than the previous FMC design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1232-1239
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• 2006

In video standards such as MPEG-1/2/4 and H.264/AVC, motion estimation / compensation(ME/MC) process causes the most encoding complexity of video encoder. The full search method, which is used in general video codecs, exhausts much encoding time because it compares current macroblock with those at all positions within search window for searching a matched block. For the alleviation of this problem, the fast search methods such as TSS, NTSS, DS and HEXBS are exploited at first. Thereafter, DS based MVFAST, PMVFAST, MAS and FAME, which utilize temporal or spacial correlation characteristics of motion vectors, are developed. But there remain the problems of image quality degradation and algorithm complexity increase. In this thesis, the proposed algorithm maximizes search speed and minimizes the degradation of image quality by determining initial search point correctly and using simple one-dimension search patterns considering motion characteristics of each frame.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.79-85
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• 2010

In video standards such as H.264/AVC, motion estimation (ME) / compensation (MC) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. The full search technique, which is used in general video codecs, gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has benn proposed. Among them, NPDS show that can maintain its video quality very close to the full search technique while achieving computation reduction by using a halfway-stop technique in the calculation of block distortion measure. In this paper, we proposed algorithm by determining minimum distortion measure with predictive motion vector and using the new search order. As the result, we can check that the proposed algorithm reduces the computational load 95% in average compared to the full search, respectively with the PSNR lost about 0.04dB.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.116-126
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• 2011

In this paper, we present a multi-media processor which can decode multiple-format video standards. The designed processor is evaluated with optimized MPEG-2, MPEG-4, and AVS (Audio video standard). There are two approaches for developing of real-time video decoders. First, hardware-based system is much superior to a processor-based one in execution time. However, it takes long time to implement and modify hardware systems. On the contrary, the software-based video codecs can be easily implemented and flexible, however, their performance is not so good for real-time applications. In this paper, in order to exploit benefits related to two approaches, we designed a processor called ASIP(Application specific instruction-set processor) for video decoding. In our work, we extracted eight common modules from various video decoders, and added several multimedia instructions to the processor. The developed processor for video decoders is evaluated with the Synopsys platform simulator and a FPGA board. In our experiment, we can achieve about 37% time saving in total decoding time.