• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.11
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• pp.12-20
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• 2002

Serially concatenated multilevel coded modulation (SCMCM) is proposed in this paper. It is a combined scheme of the outer convolutional code and inner multilevel coded modulation (MCM) which is bandwidth-efficient coded modulation. And the performance of three schemes for decoding of the proposed SCMCM is compared and analyzed. As results of simulations, global iterative decoding with inner and outer code should be performed to improve the error performance as the number of iterations is increased. And the scheme which uses both local iterative multistage decoding in MCM and global iterative decoding with inner and outer code, called Scheme 3 in this paper, shows the best error performance among the three schemes considered in this paper. In addition, performance difference between this scheme and the others is increased as the signal to noise ratio (SNR) is increased. Therefore, Scheme 3 is considered to be the proper decoding scheme of SCMCM.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.391-401
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• 2004

In this paper, we introduce a novel coding method to efficiently enable spatial random access for high resolution video. In terms of resolution and display size, standard display devices (such as cathode-ray tubes. monitors. PDAs, and LCDs) do not sufficiently support high resolution video such as digital cinema and panoramic video. Currently, users have no choice but to view video at lower resolution as a result of down-sampling, or only a partial region of the video due to display size limitations. Our proposed method. which we call the B-map, represents the set of starting locations of the coded segments in a picture frame. This information, or B-map, is first sent to the decoder prior to the coded data stream of the frame and is then used for fast local decoding. To test our method, we compare our B-map with JPEG tiling and the JPEG Resynchronization marker. Experimental results show that the proposed coding method requires less overhead than existing methods during the same decoding time. The results show promise for future panoramic or digital cinema applications.

• Journal of Computing Science and Engineering
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• v.4 no.3
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• pp.207-224
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• 2010

This paper presents a compression scheme for mesh geometry, which is suitable for mobile graphics. The main focus is to enable real-time decoding of compressed vertex positions while providing reasonable compression ratios. Our scheme is based on local quantization of vertex positions with mesh partitioning. To prevent visual seams along the partitioning boundaries, we constrain the locally quantized cells of all mesh partitions to have the same size and aligned local axes. We propose a mesh partitioning algorithm to minimize the size of locally quantized cells, which relates to the distortion of a restored mesh. Vertex coordinates are stored in main memory and transmitted to graphics hardware for rendering in the quantized form, saving memory space and system bus bandwidth. Decoding operation is combined with model geometry transformation, and the only overhead to restore vertex positions is one matrix multiplication for each mesh partition. In our experiments, a 32-bit floating point vertex coordinate is quantized into an 8-bit integer, which is the smallest data size supported in a mobile graphics library. With this setting, the distortions of the restored meshes are comparable to 11-bit global quantization of vertex coordinates. We also apply the proposed approach to compression of vertex attributes, such as vertex normals and texture coordinates, and show that gains similar to vertex geometry can be obtained through local quantization with mesh partitioning.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.93-101
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• 2017

This paper proposes an algorithm for adaptive loop filter (ALF) complexity reduction in the decoding process. In the original ALF algorithm, filtering for I frames is performed in the frame unit, and thus, all of the pixels in a frame are filtered if the current frame is an I frame. The proposed algorithm is designed on top of the local gradient calculation. On both the encoder side and the decoder side, homogeneous areas are checked and skipped in the filtering process, and the filter coefficient calculation is only performed in the inhomogeneous areas. The proposed algorithm is implemented in Joint Exploration Model (JEM) version 3.0 future video coding reference software. The proposed algorithm is applied for frame-level filtering and intra configuration. Compared with the JEM 3.0 anchor, the proposed algorithm has 0.31%, 0.76% and 0.73% bit rate loss for luma (Y) and chroma (U and V), respectively, with about an 8% decrease in decoding time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.58-64
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• 2016

In this paper presents Robust k-means clustering-based high-speed bar code decoding method to blur and lighting. for fast operation speed and robust decoding to blur, proposed method uses adaptive local threshold binarization methods that calculate threshold value by dividing blur region and a non-blurred region. Also, in order to prevent decoding fail from the noise, decoder based on k-means clustering algorithm is implemented using area data summed pixel width line of the same number of element. Results of simulation using samples taken at various worst case environment, the average success rate of proposed method is 98.47%. it showed the highest decoding success rate among the three comparison programs.

• Journal of the Semiconductor & Display Technology
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• v.8 no.2
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• pp.23-29
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• 2009

To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1378-1391
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• 2019

In recent years, automatic document summarization has been widely studied in the field of natural language processing thanks to the remarkable developments made using deep learning models. To decode a word, existing models for abstractive summarization usually represent the context of a document using the weighted hidden states of each input word when they decode it. Because the weights change at each decoding step, these weights reflect only the local context of a document. Therefore, it is difficult to generate a summary that reflects the overall context of a document. To solve this problem, we introduce the notion of a general context and propose a model for summarization based on it. The general context reflects overall context of the document that is independent of each decoding step. Experimental results using the CNN/Daily Mail dataset show that the proposed model outperforms existing models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.148-154
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• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard are required a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method is reduced number of unnecessary iteration. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.517-527
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• 2012

This paper considers a cooperative communication system with a single relay node, where two-layer superposition coding and successive decoding is employed to reduce the expected distortion of a Gaussian source delivered. For the system, we propose a relay scheme which forwards an appropriate relay signal at the relay node, based on the local decoding result of layers and the decoding result of layers at the destination node fed back to the relay node. In the scheme, the relay signal is designed not only by applying decode-and-forward but also by applying amplify-and-forward to reduce the outage probability in final decoding of each layer. The performance of the proposed scheme is evaluated numerically in terms of the expected distortion at various relay locations using outage probabilities derived. The results show that the proposed scheme outperforms the conventional schemes in most cases of the relay location and the gain gets larger when the relay node is closer to the source node in particular.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.463-471
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• 2019

This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.