• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.335-343
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• 2001

The conventional wavelet-based fractal image coding has the disadvantage that the encoding takes a long time, since each range block finds the best domain in the image. In this Paper, we propose wavelet-based fractal image coding using SAS(Self Affine System) method and multi-scale factor. It consists of the range and domain blocks in DWT(discrete wavelet transform) region. Using SAS method, the proposed method is that the searching process of the domain block is not required, and the range block selects the domain which is relatively located the same position in the upper level. The proposed method can perform a fast encoding by reducing the computational complexity in the encoding process. In order to improve the disadvantage of SAS method which is reduced image qualify, the proposed method is improved image qualify using the different scale factors for each level. As a result, there is not influence on an image quality, the proposed method is enhanced the encoding time and compression ratio, and it is able to the progressive transmission.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.207-210
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• 2009

An efficient algorithm to compress high dynamic range (HDR) videos is proposed in this work. We separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence. Then, we encode those two sequences using the standard H.264/AVC codec. During the encoding, we allocate a limited amount of bit budget to the LDR sequence and the ratio sequence adaptively to maximize the qualities of both the LDR and HDR sequences. While a conventional LDR decoder uses only the LDR stream, an HDR decoder can reconstruct the HDR video using the LDR stream and the ratio stream. Simulation results demonstrate that the proposed algorithm provides higher performance than the conventional methods.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3462-3469
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• 2000

In this paper,new image vector quantization method for improvemtnt computation cost and compression ratio is proposed. A proposed method could saved the cornputatio cost of codebook eneration and encoding using partial codebook search, partial codevector elements, and interuplion criterion. And to improve cornpression ratio of codegook index lossless coding, codebook rearrangement, and variable length coding scheme are used.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.45-54
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• 2002

This paper proposes a video compression algorithm using characteristics of wavelet coefficients. The proposed algorithm can provide lowed bit rate and faster running time while guaranteeing the reconstructed image qualify by the human virtual system. In this approach, each video sequence is decomposed into a pyramid structure of subimages with various resolution to use multiresolution capability of discrete wavelet transform. Then similarities between two neighboring frames are obtained from a low-frequency subband which Includes an important information of an image and motion informations are extracted from the similarity criteria. Four legion selection filters are designed according to the similarity criteria and compression processes are carried out by encoding the coefficients In preservation legions and replacement regions of high-frequency subbands. Region selection filters classify the high-frequency subbands Into preservation regions and replacement regions based on the similarity criteria and the coefficients In replacement regions are replaced by that of a reference frame or reduced to zero according to block-based similarities between a reference frame and successive frames. Encoding is carried out by quantizing and arithmetic encoding the wavelet coefficients in preservation regions and replacement regions separately. A reference frame is updated at the bottom point If the curve of similarity rates looks like concave pattern. Simulation results show that the proposed algorithm provides high compression ratio with proper Image quality. It also outperforms the previous Milton's algorithm in an Image quality, compression ratio and running time, leading to compression ratio less than 0.2bpp. PSNR of 32 dB and running tome of 10ms for a standard video image of size 352${\times}$240 pixels.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.388-397
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• 2015

High Efficiency Video Coding (HEVC)/H.265 is a new video coding standard which is known as high compression ratio compared to the previous standard, Advanced Video Coding (AVC)/H.264. Due to achievement of high efficiency, HEVC sacrifices the time complexity. To apply HEVC to the market applications, one of the key requirements is the fast encoding. To achieve the fast encoding, exploiting thread-level parallelism is widely chosen mechanism since multi-threading is commonly supported based on the multi-core computer architecture. In this paper, we implement both the Tile-level parallelism and the Frame-level parallelism for HEVC encoding on multi-core platform. Based on the implementation, we present two approaches in combining the Tile-level parallelism with Frame-level parallelism. The first approach creates the fixed number of tile per frame while the second approach creates the number of tile per frame adaptively according to the number of frame in parallel and the number of available worker threads. Experimental results show that both improves the parallel scalability compared to the one that use only tile-level parallelism and the second approach achieves good trade-off between parallel scalability and coding efficiency for both Full-HD (1080 x 1920) and 4K UHD (3840 x 2160) sequences.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.409-418
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• 1999

The fractal image compression is based on the self-similarity that some area in an image exhibits a very similar shape with other areas. This compression technique has very long encoding time although it has high compression ratio and fast decompression. To cut-off the encoding time, most researches have restricted the search of domain blocks for a range block. These researches have been mainly focused on the coherence between a domain block and a range block, while they have not utilized the coherence among range blocks well. Therefore, we give an analysis on the coherence among range blocks in order to develope an efficient fractal Image compression algorithm. We analysis the range blocks according to not only measures for defining the range block coherence but also threshold of each measure. If these results are joined in a prior work of other fractal compression algorithms, it will give a great effectiveness in encoding time.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.328-338
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• 2008

Multi-view video coding (MVC) based on H.264/AVC encodes multiple views efficiently by using a prediction scheme that exploits inter-view correlation among multiple views. However, with the increase of the number of views and use of inter-view prediction among views, total encoding time will be increased in multiview video coding. In this paper, we propose a fast mode decision using both MB(Macroblock)-based region segmentation information corresponding to each view in multiple views and global disparity vector among views in order to reduce encoding time. The proposed method achieves on average 40% reduction of total encoding time with the objective video quality degradation of about 0.04 dB peak signal-to-noise ratio (PSNR) by using joint multi-view video model (JMVM) 4.0 that is the reference software of the multiview video coding standard.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.19-27
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• 2001

The conventional fractal image compression based on wavelet transform has the disadvantage that the encoding takes many time, since it finds the optimum domain for all the range blocks. In this paper, we propose the fractal image compression based on wavelet transform using the SAS(Self Affine System) techniques. It consists of the range and domain blocks in the wavelet transform, and the range blocks select the domain which is located the relatively same position. In the encoding process, the proposed methods introduce SAS techniques that the searching process of the domains blocks is not required. Therefore, it can perform a fast encoding by reducing the computational complexity. And, the image quality is improved using the different scale factors for each level and the sub-tree in the decoding. As a result, the image quality and the compression ratio are adjustable by the scale factors.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.857-865
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• 1995

In this paper, a nibble RLE(Run Length Encoding) code for real time compression and decompression of Hanguel bit map font and printer data is proposed. The nibble RLE code shows good compression ratio in complete form Hangeul Myoungjo and Godik style bit map font and printer output bit map data. And two ASICs seperating compression and decompression are designed and simulated on CAD to verify the proposed code. The 0.8 micron CMOS Sea of Gate is used to implement the ASICs in amount of 2, 400 gates, and these are running at 25MHz. Therefore, the proposed code could be implemented with simple hardware and performs 100M bit/sec compression and decomression at maximum, it is good for real time applications.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.243-247
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• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).