• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.650-652
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• 2022

Frame rate up-conversion (FRUC) algorithm is an image interpolation technology that improves the frame rate of moving pictures. This solves problems such as screen shake or blurry motion caused by low frame rate video in high-definition digital video systems, and provides viewers with a more free and smooth visual experience. In this paper, we propose a video compression technique using deep learning-based FRUC algorithm. The proposed method compresses and transmits after excluding some images from the original video, and uses a deep learning-based interpolation method in the decoding process to restore the excluded images, thereby compressing them with high efficiency. In the experiment, the compression performance was evaluated using the decoded image and the image restored by the FRUC algorithm after encoding the video by skipping 1 or 3 pages. When 1 and 3 sheets were excluded, the average BD-rate decreased by 81.22% and 27.80%. The reason that excluding three images has lower encoding efficiency than excluding one is because the PSNR of the image reconstructed by the FRUC method is low.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.170-176
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• 2010

Prediction is an important step in high-performance lossless data compression. In this paper, we propose a novel lossless image coding algorithm to increase prediction accuracy which can display low-resolution images quickly with a multi-resolution image technique. At each resolution, we use pixels of the previous resolution image to estimate current pixel values. For each pixel, we determine its estimated value by considering horizontal, vertical, diagonal edge information and average, weighted-average information obtained from its neighborhood pixels. In the experiment, we show that our method obtains better prediction than JPEG-LS or HINT.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1273-1278
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• 2012

In this paper, we introduce modified integer transforms for lossless image compression and evaluate their performances for two-dimensional transforms. The two-dimensional extensions of the modified integer transforms show different performances in terms of coding efficiency and computational complexity. Thus, we measure performances for two-dimensional separable transforms and a two-dimensional non-separable transform. The separable modified integer transform used in H.264, the modified integer transform using the lifting scheme, and the non-separable transform in JPEG XR are evaluated in this paper. Also, experiments and their results are given. The experimental results indicate that the modified integer transform using the lifting scheme shows the best performance in terms of compression efficiency.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.519-528
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• 2016

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.43-51
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• 2014

Multi-view video including depth image is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This efficient method to compress new contents is suggested to use layered depth image representation and to apply for video compression encoding by using 3D warping. This paper proposed enhanced compression method using layered depth image representation and H.264/AVC video coding technology. In experimental results, we confirmed high compression performance and good quality of reconstructed image.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.500-509
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• 2001

Image compression based on Wavelet gives much better quality than JPEG based on DCT, but suffers from ringing or blurring effects around edges as the compression is increased. In this paper, we proposed enhanced image compression by pre-processing wavelet coefficients. This pre-processing is performed by making a low threshold and enhanced by zerotree scan method when subband's zerotrees are established. It might increase significants coefficient by means of modifying the threshold and reflect on the orientation of subbands. Some experimental results show our method is more efficient than the conventional methods, JPEG. And then the developed coding scheme improves the quality of images and visually shows more pleasing results for most practical images.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.136-139
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• 2017

Recently, many companies and consumers has shown a lot of interest toward VR(Virtual Reality), so many VR devices such as HMD(Head mounted Display) and 360 degree VR camera are released on the market. Current encoded 360 degree VR video uses the codec which originally made for the conventional 2D video. Therefore, the compression efficiency isn't optimized because the en/decoder does not consider the characteristics of the 360 degree VR video. In this paper, we propose a method to improve the compression efficiency by using the reference frame which compensates for the distortions caused by characteristics the 360 degree VR video. Applying the proposed method we were able to increase the compression efficiency by providing better prediction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.97-104
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• 2006

The state-of-the-art H.264/AVC standard was designed for the lossy video coding so that it could not yield the best performance for lossless video coding. In this paper, we propose two efficient intra lossless coding methods by embedding a pixel-wise prediction into the H.264/AVC. One is based on the pixel-wise prediction for the residual signal of the H.264/AVC intra Prediction and the other suggests a newly additional intra prediction mode for the conventional intra prediction. We found that the proposed lossless coding algorithms could achieve approximately $12%{\sim}25%$ more bit saving compared to the H.264/AVC FRExt high profile for several test sequences in terms of a compression ratio.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1036-1046
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• 2011

MPEG and VCEG have constituted a collaboration team called JCT-VC(Joint Collaborative Team on Video Coding) and have been developing HEVC(High Efficiency Video Coding) standard. All transform coefficients in a TU(Transform Unit) have been equally quantized according to the quantization and inverse quantization method which is used in HEVC standard. Such an equal quantization is not efficient because the transformed coefficients in the TU are not eqully distributed. Furthermore, the quantized coefficients which is positioned in later scanning order cannot be efficient due to the entropy scanning method. We suggest an algorithm that transform coefficients are quantized at different values according to the position in TU considering a scanning order of entropy encoding to improve the coding efficiency. The principle of this algorithm is that quantization and inverse quantization are carried out according to the scanning order which is in accordance with the statistical characteristic of distribution of quantized transform coefficients. The proposed algorithm shows on the average of 0.34% Y BD-rate compression rate improvement.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.559-566
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• 2012

In this paper, we propose a fast fractal image coding algorithm to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make the corresponding image to be compared with. Then, the whole area of the contracted image is searched in order to find the fixed point of contractive transformation of the original image corresponding to the contracted image. It needs a lot of searching time on encoding. However, the proposed algorithm considerably reduces encoding time by using scaling method and limited search area method. On comparison of the proposed algorithm with Jacquin's method, the proposed algorithm is dozens of times as fast as that of Jacquin's method on encoding time with a little degradation of the decoded image quality and a little increase of the compression rate. Therefore, it is found that the proposed algorithm largely improves the performance in the aspect of encoding time when compared with other fractal image coding methods.