• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.736-739
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• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• 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].

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.183-189
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• 2013

This paper proposes a novel lossless image compression scheme composed of direction-adaptive prediction and context-based entropy coding. In the prediction stage, we analyze the directional property with respect to the current coding pixel and select an appropriate prediction pixel. In order to further reduce the prediction error, we propose a prediction error compensation technique based on the context model defined by the activities and directional properties of neighboring pixels. The proposed scheme applies a context-based Golomb-Rice coding as the entropy coding since the coding efficiency can be improved by using the conditional entropy from the viewpoint of the information theory. Experimental results indicate that the proposed lossless image compression scheme outperforms the low complexity and high efficient JPEG-LS in terms of the coding efficiency by 1.3% on average for various test images, specifically for the images with a remarkable direction the proposed scheme shows better results.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.307-315
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• 2014

A new modified lossless intra-coding method based on a cross residual transform is applied to HEVC(High Efficiency Video Coding). The HEVC standard including a multi-directional spatial prediction method to reduce spatial redundancy encodes the pixels in a PU (Prediction Unit) by using neighboring pixels. In the new modified lossless intra-coding method, the spatial prediction is performed by pixel-based DPCM but is implemented by block-based manner by using cross residual transform on the HEVC standard. The experimental results show that the new lossless intra-coding method reduces the bit rate of approximately 8.4% in comparison with the lossless-intra coding method in the HEVC standard and the proposed method results in slightly better compression ratio than the JPEG2000 lossless coding.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.203-204
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• 2007

In this work, we propose a compression algorithm for depth images, which are obtained from multi-view sequences. The proposed algorithm represents a depth image using a 3-D regular triangular mesh and predictively encodes the mesh vertices using a linear prediction scheme. The prediction errors are encoded with a arithmetic coder. Simulation results demonstrate that the proposed algorithm provides better performances than the JPEG2000 lossless coder.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.763-770
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• 2000

In this paper, a new stereo image compression algorithm is suggested in which the residual image extracted from the stereo image by the disparity-compensated prediction method is compressed using the wavelet transform considering the inter & intra correlation between subbands. The compression performance of the proposed method is significantly improved by comparing with the conventional algorithm such as EPIC, EPWIC & JPEG through the computer simulation and the PSNR is also increased about 3.5dB compared with the EPIC. Finally, the stereo image having a good 3D effect can be reconstructed from the compressed image data by the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4557-4572
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• 2020

The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis. Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines. In this paper, we propose a method to ensemble multiple deep learning steganalyzers. We select SRNet and RESDET as our base models. Then we design a three-layers model ensemble network to fuse these base models and output the final prediction. By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved. The proposed method won second place in the Alaska 1 competition in the end.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3885-3895
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• 2000

The emergence of digital imaging and digital networks has made duplication of original artwork easier. In order to protect these creations, new methods for signing and copyrighting visual data are needed. In the last few years, a large number of schemes have heen proposed for hiding copyright marks and other information in digital image, video, audio and other multimedia objects. In this paper, we propose a technique for embedding the watermark of visually recognizable patterns into the frequency domain of images. The embedded watermark can be retrieved from the decoded sequence witbout knowledge of the original. Because the source image is not required to extract the watermark, one cannot make the fake original that is invertible to watermarking scheme from the waternlarked image. In order to recover the embedded signature data without knowledge of the original, a prediction of the original value of the pixel containing the information is needed. The prediction is based on a averaging of amplitude values in a neighborhood around the pixel itself. Additionally the projxJsed technique could survive several kinds of image processings including JPEG lossy compression.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.405-408
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• 2005

This paper proposed the method to images of losses using restorable wavelet transformation. The algorithm proposed in this work stars by processing the pre-quantizer on the original images to organize an image that matches the gray level. The wavelet transformation filter to the original image which is already pre-quantized in order to segment bands. Considering the lowest coding of bands influencing the most to the overall condition of the reconstructed image, it only uses the Huffman coding using prediction. Reconstructed images by proposed algorithm showed higher PSNR when coding images of JPEG or non pre-quantized images. Applying pre-quantizer can control the peak errors and is expected to be useful at mass image compression.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.48-52
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• 2012

As the growing popularity of smartphones, mobile web browsing has become one of the most important and popular applications in mobile devices. Furthermore, it is clear that the demand for PC-like full browser performance on mobile devices is increasing greatly. WebKit is an open source web browser engine adopted by Google Android. This paper proposed a technique of increasing the performance of WebKit by paralleling its libraries. This method was applied to JPEG library and the performance evaluation was conducted in PC environment. The results was used to estimate the performance prediction on multi-core mobile embedded architecture and to show the feasibility of the proposed method to estimate the performance gain on heterogeneous multi-core embedded architecture.