• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.358-360
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• 2004

The digital images contain a significant amount of redundancy and require a large amount of data for their storage and transmission. Therefore, the image compression is necessary to treat digital images efficiently. The goal of image compression is to reduce the number of bits required for their representation. The image compression can reduce the size of image data using contractive mapping of original image. Among the compression methods, the mapping is affine transformation to find the block(called range block) which is the most similar to the original image. In this paper, we applied the neural network(SOM) in encoding. In order to improve the performance of image compression, we intend to reduce the similarities and unnecesaries comparing with the originals in the codebook. In standard image coding, the affine transform is performed with eight isometries that used to approximate domain blocks to range blocks.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.143-151
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• 2016

This paper presents new prediction methods to improve compression performance of the so-called near-lossless RGB-domain image coder, which is designed to effectively decrease the memory bandwidth of a system-on-chip (SoC) for image processing. First, variable block size (VBS)-based intra prediction is employed to eliminate spatial redundancy for the green (G) component of an input image on a pixel-line basis. Second, inter-color prediction (ICP) using spectral correlation is performed to predict the R and B components from the previously reconstructed G-component image. Experimental results show that the proposed algorithm improves coding efficiency by up to 30% compared with an existing algorithm for natural images, and improves coding efficiency with low computational cost by about 50% for computer graphics (CG) images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.124-132
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• 1994

An image data compression method for a digital VCR must satisfy special requirements such as high speed playback. various edting capabilities and error concealment to provide immunity to tape dropouts. Taking these requirements requirements into consideration, this paper proposes a new interframe subband coding algorithm for a digital VCR. In the proposed method, continuous input images are fist partitioned into four frequency bands. The lowest frequency subband is coded with 3-D block adaptive quantization that removes the level redundancy within each level. The other higher frequency subbands are coded by an intraframe coding method using the property of the human visual system. To keep reasonable image quality in high speed palyback, a segment forming method in the frequency domaing is also proposed Computer simulation results demonstrate that the proposed algorithm has the potential of achieving virtually lossless compression in normal play and produces an image with less mosaic errors in high speed play.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.323-326
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• 2016

High Efficiency Video Coding (HEVC) adopts intra transform skip mode, in which a residual block is directly quantized in the pixel domain without transforming the block into the frequency domain. Intra transform skip mode provides a significant coding gain for screen content. However, when intra-prediction errors are not transformed, the errors are often correlated along the intra-prediction direction. This paper introduces a residual differential pulse code modulation (DPCM) method for the intra-predicted and transform-skipped blocks to remove redundancy. The proposed method performs pixel-by-pixel residual prediction along the intra-prediction direction to reduce the dynamic range of intra-prediction errors. Experimental results show that the transform skip mode's Bjøntegaard delta rate (BD-rate) is improved by 12.8% for vertically intra-predicted blocks. Overall, the proposed method shows an average 1.2% reduction in BD-rate, relative to HEVC, with negligible computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5063-5073
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• 2016

In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.11
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• pp.30-36
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• 2010

In recent memories, repair is an unavoidable method to maintain its yield and quality. Although many word oriented memories as well as embedded memories in system-on-chip (SOC) consists of multiple local memory blocks with a global spare architecture, most of previous studies on built-in redundancy analysis (BIRA) algorithms have focused on single memory block with a local spare architecture. In this paper, a new BIRA algorithm for multiple blocks with a global spare architecture is proposed. The proposed BIRA is basd on CRESTA which is able to achieve optimal repair rate with almost zero analysis time. In the proposed BIRA, all repair solutions for local memory blocks are analyzed by local analyzers which belong to each local memory block and then compared sequentially and judged whether each solution can meet the limitation of the global spare architecture or not. Experimental results show that the proposed BIRA achieves much faster analysis speed compared to previous BIRAs with an optimal repair rate.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.188-191
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• 2002

To reduce the bit-rate of video sequences by removing temporal redundancy, motion estimation techniques have been developed. However, the high computational complexity of the problem makes such techniques very difficult to be applied to high-resolution applications in a real time environment. For this reason, low computational complexity motion estimation algorithms are viable solutions. If a priori knowledge about the motion of the current block is available before the motion estimation, a better starting point for the search of n optimal motion vector on be selected and also the computational complexity will be reduced. In this paper, we present an adaptive block matching algorithm based on temporal correlations of consecutive image frames that defines the search pattern and the location of initial starting point adaptively to reduce computational complexity. Experiments show that, comparing with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(㏈) better than DS in terms of PSNR and improves as much as 50% in terms of the average number of search points per motion estimation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.64-72
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• 1995

We propose a new image coding method which takes into account both statistical redundancy and perceptual irrelevancy of the DCT coefficients so as to provide a high quality of the reconstructed images with a reduced transmission bit rate First, a block of DCT coefficients are decomposed into 16 subvectors so as for a subvector to convey key information about one of the low-pass or the dirctional filtered images. Then, the most significant subvector is selected as the principal edge of the block and then vector quantized. After that, the residuals of the block are computed and then sequentially quantized through aforementioned procedure until the quantization distortion is smaller than the target distortion. The proposed scheme is good at encoding images with a variety of transmission bit rates, especially at very low bit rate coding. In addition, it is another benifit of the proposed scheme that an image can be quantized with a wide range of the transmission bit rates by simply adapting the stopping criterion of the sequential vector quantizer according to the target distortion of the reconstructed image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.258-262
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• 2009

In this paper, we propose an effective memory reduction algorithm to reduce the amount of reference frame buffer and memory bandwidth in video encoder and decoder. In general video codecs, decoded previous frames should be stored and referred to reduce temporal redundancy. Recently, reference frames are recompressed for memory efficiency and bandwidth reduction between a main processor and external memory. However, these algorithms could hurt coding efficiency. Several algorithms have been proposed to reduce the amount of reference memory with minimum quality degradation. They still suffer from quality degradation with fixed-bit allocation. In this paper, we propose an adaptive block-based min-max quantization that considers local characteristics of image. In the proposed algorithm, basic process unit is $8{\times}8$ for memory alignment and apply an adaptive quantization to each $4{\times}4$ block for minimizing quality degradation. We found that the proposed algorithm could improve approximately 37.5% in coding efficiency, compared with an existing memory reduction algorithm, at the same memory reduction rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.386-393
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• 2004

In order to maintain load balancing in distributed systems in a decentralized manner, every node should obtain workload information from all the nodes on the network. It requires $Ο({v^2})$ traffic overheads, where v is the number of nodes. This paper presents a new synchronous dynamic distributed load balancing algorithm for a ( v,k+1,1)-configured network topology, which is a kind of 2k regular graph, based on symmetric balanced incomplete block design, where v equals ${k^2}+k+1$. Our algorithm needs only Ο(v√v) message overheads and each node receives workload information from all the nodes without redundancy. And load balancing in this algorithm is maintained so that every link has same amount of traffic by √v for transferring workload information.