• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.434-442
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• 2015

In this paper, we propose an integrated spatial and view scalable video codec based on high efficiency video coding (HEVC). The proposed video codec is developed based on similarity and uniqueness between the scalable extension and 3D multi-view extension of HEVC. To improve compression efficiency using the proposed scalable multi-view video codec, inter-layer and inter-view predictions are jointly employed by using high-level syntaxes that are defined to identify view and layer information. For the inter-view and inter-layer predictions, a decoded picture buffer (DPB) management algorithm is also proposed. The inter-view and inter-layer motion predictions are integrated into a consolidated prediction by harmonizing with the temporal motion prediction of HEVC. We found that the proposed scalable multi-view codec achieves bitrate reduction of 36.1%, 31.6% and 15.8% on the top of ${\times}2$, ${\times}1.5$ parallel scalable codec and parallel multi-view codec, respectively.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3028-3030
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• 2000

In general. a speech coding is dedicated to the compression performance or the speech quality. But. the speech coding in this paper is focused on the performance of flexible transmission to the, network speed. For this. the subbanding coding is needed. which is used the wavelet packet concept in the signal analysis. The extraction of each frequency-band is difficult to general signal analysis methods, after coding each band, the reconstruction of these is also a difficult problem. But. with the wavelet packet concept(perfect reconstruction) and its fast computation algorithm. the extraction of each band and the reconstruction are more natural. Also, this paper describes a direct solution of the voice transmission on network and implement this algorithm at the TCP/IP network environment of PC.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.69-71
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• 2016

본 논문에서는 JPEG, MPEG 등 표준압축 기술에 사용되고 있는 무손실 압축 기법 중 Huffman coding 을 통해 영문 텍스트를 압축하고 압축률을 구해보았다. 각 글자를 Huffman coding 의 원리에 기초하여 빈도수에 따라 코드를 결정한다. 결정된 코드에 따라 영문 텍스트를 변환하여 압축을 진행한다. 본 연구에서는 MATLAB을 이용하여 영문 텍스트의 각 글자 빈도수를 구하였고 Huffman coding 과정을 수행하였다. 또한 영문 텍스트를 코드로 변환과정을 수행하여 아스키코드와 압축률을 비교하였다. Huffman coding 은 아스키코드만으로 이용하는 것보다 1.89:1 의 압축률을 나타내었다.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.322-331
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• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.

• 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.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.55-68
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• 2000

Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.917-923
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• 2011

In this paper, a new prediction based embedded compression (EC) codec algorithm for the JPEG2000 encoder system is proposed to reduce excessive memory requirements. The EC technique can reduce the 50 % memory requirement for intermediate low-frequency coefficients during multiple discrete wavelet transform (DWT) stages compared with direct implementation of the DWT engine of this paper. The LOCO-I predictor and MAP are widely used in many lossless picture compression codec. The proposed EC algorithm use these predictor which are very simple but surprisingly effective. The predictive EC scheme adopts a forward adaptive quantization and fixed length coding to encoding the prediction error. Simulation results show that our LOCO-I and MAP based EC codecs present only PSNR degradation of 0.48 and 0.26 dB in average, respectively. The proposed algorithm improves the average PSNR by 1.39 dB compared to the previous work in [9].

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.77-83
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• 2012

In this paper, a low-complexity embedded compression (EC) Codec algorithm for the wavelet video coder is applied to reduce excessive external memory requirements. The EC algorithm is used to achieve a fixed compression ratio of 50 % under the near-lossless-compression constraint. The EC technique can reduce the 50 % memory requirement for intermediate low-frequency coefficients during multiple discrete wavelet transform stages compared with direct implementation of the wavelet video encoder of this paper. Furthermore, the EC scheme based on a forward adaptive quantization and fixed length coding can save bandwidth and size of buffer between DWT and SPIHT to 50 %. Simulation results show that our EC algorithm present only PSNR degradation of 0.179 and 0.162 dB in average when the target bit-rate of the video coder are 1 and 0.5 bpp, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.961-967
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• 2009

In this paper, the lossless compression method is proposed for an 8-bit bitplane of the input image. The lower bitplanes are not well compressed because of irregularity of pixels. To overcome these drawbacks, this paper propose a mixed coding method that using the block-based lossless compression and the bit-based losselss compression, introducing the H. 264 and the JBIG. First, to take advantage of the characteristics of the bitplanes, 8-bitplane against the top 4 bits and lower 4 bits were separated. Next, the JBIG compression method was used in separated top 4-bitplane because of a lot of correlation between bits. And a separated lower 4-bitplane was applied the improved method that using the H. 264 lossless prediction. A pre-processing method applied to the lower 4-bitplane then irregular distribution of pixel values are converted to regular. Using the proposed method to test for various test images were performed. Experimental results from a printer using 8-bit image compared to JBIG average 19%, lower 4bit image compression performance with an average of 11% could be obtained.