• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.12
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• pp.3033-3045
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• 1996

In this paper, we propse an object-oriented coding method in low bit-rate channels using pyramid structure and residual image compensation. In the motion estimation step, global motion is estimated using a set of multiresolution images constructed in a pyramid structure. We split an input image into two regions based on the gradient value. Regions with larte motions obtain observation points at low resolution level to guarantee robustness to noise and to satisfy a motion constraint equation whereas regions with local motions such as eye, and lips get observation points at the original resolution level. Local motion variations and intesity variations of an image reconstructed by the golbal motion are compensated additionally by using the previous residual image component. Finally, the model failure (MF) region is compensated by the pyramid mapping of the previous displaced frame difference (DFD). Computer simulation results show that the proposed method gives better performance that the convnetional one in terms of the peak signal to noise ratio (PSNR), compression ratio (CR), and computational complexity.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.100-108
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• 2023

In hybrid block-based video coding, transform coding converts spatial domain residual signals into frequency domain data and concentrates energy in a low frequency band to achieve a high compression efficiency in entropy coding. The state-of-the-art video coding standard, VVC(Versatile Video Coding), uses DCT-2(Discrete Cosine Transform type 2), DST-7(Discrete Sine Transform type 7), and DCT-8(Discrete Cosine Transform type 8) for primary transform. In this paper, considering that DCT-2, DST-7, and DCT-8 are all linear transformations, we propose an inverse transform that reduces the number of multiplications in the inverse transform by using the linearity of the linear transform. The proposed inverse transform method reduced encoding time and decoding time by an average 26%, 15% in AI and 4%, 10% in RA without the increase of bitrate compared to VTM-8.2.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.67-76
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• 2012

Expanding services and productions for screen content videos recently, necessity of new compression techniques is emerging. The next-generation video coding standard is also considering specified coding tools for screen content videos, but it is still preliminary stage. In this paper, we investigate the characteristics of screen content videos for which we propose the quantization in spatial domain to improve coding efficiency. The proposed method directly employs quantization for residual signal without any transformations. The proposed method also applies adaptive coefficients prediction and in-loop filter for quantized residual signals in spatial domain based on the characteristics of screen content videos. As a results, the proposed method for the random access, the low-delay and the all-intra modes achieve bit-saving about 4.4%, 5.1%. and 4.9%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.87-94
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• 2007

Imbalances in focus, luminance and color between stereo Pairs could cause disparity vector estimation error and increment of transmission data. If the distribution of errors in residual image is large, it may influence to lowering of compression performance. Therefore, in this paper, we propose an efficient balancing method between stereo pairs to reduce the effect. For this, we registrated stereo images using a FFT based method to consider the pixels in the occluded region, we eliminated the pixels of blocks which has large error of disparity vector estimation in balancing function estimation. The balancing function has estimated using histogram specification, local information of target image and residual image between stereo images. Experiments show that the proposed method is effective in error distribution, PSNR and disparity vector estimation. We expect that our method can be improving compression efficiency in stereo coding system.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.610-617
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• 2009

An overview of various modes and tools of MPEG Surround is provided Because the binaural mode of MPEG Surround supports the virtual 5.1-channel playback based on HRTFs, it can be played via headphones and earphones for portable audio devices. MPEG Surround also supports the enhanced matrix mode which converts stereo signals to 5.1-channel signals without side information, the 3D stereo mode which deals with 3D-coded signals, the low power version which greatly reduces the computational load in the decoding process. Besides, MPEG Surround provides the arbitrary downmix gains (ADGs) tool which is applied to artistic downmix signals, the matrix compatibility tool which is applied to downmix signals by conventional matrix-based methods, the residual coding tool -which can be used at high bit rates, and the GES tool which is applied to specific sound such as applause. The listening test results by various companies and organizations are also presented for important modes and tools.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1700-1721
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• 2017

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.87-91
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• 2009

Welding is one of the most important joining processes and the effect of welding residual stresses in the structure has a great deal of influence on its quality. In this paper, recent development in computational welding mechanics, particularly calculation of welding residual stresses, is introduced. The hypoelastic formulation of finite element analysis for thermoelastic-plastic deformation is applied to welding processes to find residual deformations and stresses. Leblond's phase evolution equation coupled with the energy equation is employed to calculate the phase volume fraction; this plays an important role as a kinetics parameter affecting phase fraction effects in the mechanical constitutive equation of welded materials. Furthermore, transformation plasticity is taken into account for an accurate evaluation of stress. The influence of the phase transformation and the transformation plasticity on residual stress is investigated by means of numerical analyses using metallurgical parameters in Leblond's phase evolution equation that are adjusted with respect to various cooling rates in a CCT-diagram. Coding implementation is conducted by way of the ABAQUS user subroutines, UMAT.

• 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 the Korean Association of Geographic Information Studies
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• v.3 no.1
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• pp.1-11
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• 2000

The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.