• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.278-281
• /
• 2009

In this paper, we propose a fast partial distortion algorithm using normalized dithering matching scan to get uniform distribution of partial distortion which can reduce only unnecessary computation significantly. Our algorithm is based on normalized dithering order matching scan and calibration of threshold error using LOG value for each sub-block continuously for efficient elimination of unlike candidate blocks while keeping the same prediction quality compared with the full search algorithm. Our algorithm reduces about 60% of computations for block matching error compared with conventional PDE (partial distortion elimination) algorithm without any prediction quality, and our algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.4-7
• /
• 2022

Recently, multi-view depth estimation methods using deep learning network for the 3D scene reconstruction have gained lots of attention. Multi-view video contents have various characteristics according to their camera composition, environment, and setting. It is important to understand these characteristics and apply the proper depth estimation methods for high-quality 3D reconstruction tasks. The camera setting represents the physical distance which is called baseline, between each camera viewpoint. Our proposed methods focus on deciding the appropriate depth estimation methodologies according to the characteristics of multi-view video contents. Some limitations were found from the empirical results when the existing multi-view depth estimation methods were applied to a divergent or large baseline dataset. Therefore, we verified the necessity of obtaining the proper number of source views and the application of the source view selection algorithm suitable for each dataset's capturing environment. In conclusion, when implementing a deep learning-based depth estimation network for 3D scene reconstruction, the results of this study can be used as a guideline for finding adaptive depth estimation methods.

• The KIPS Transactions:PartB
• /
• v.12B no.2 s.98
• /
• pp.131-136
• /
• 2005

Motion Estimation (ME) has been developed to remove redundant data contained in a sequence of image. And ME is an important part of video encoding systems, since it can significantly affect the qualify of an encoded sequences. Generally, ME consists of two stages, the integer pixel motion estimation and the half pixel motion estimation. Many methods have been developed to reduce the computational complexity at the integer pixel motion estimation. However, the studies are needed at the half pixel motion estimation to reduce the complexity. In this paper, a method based on the correlations between integer pixel motion vectors and half pixel motion vectors is proposed for the half pixel motion estimation. The proposed method has less computational complexity than the full half pixel search method (FHSM) that needs the bilinear interpolation of half pixels and examines nine half pixel points to the find the half pixel motion vector. Experimental results show that the speedup improvement of the proposed method over FHSM can be up to $2.5\~80$ times faster and the image quality degradation is about to $0.07\~0.69(dB)$.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.10
• /
• pp.1845-1852
• /
• 2008

The key elements of inter prediction are motion estimation(ME) and motion compensation(MC). Motion estimation is to find the optimum motion vectors, not only by using a distance criteria like the SAD, but also by taking into account the resulting number of 비트s in the 비트 stream. Motion compensation is compensate for movement of blocks of current frame. Inter-prediction Encoding is always the main bottleneck in high-quality streaming applications. Therefore, in real-time streaming applications, dedicated hardware for executing Inter-prediction is required. In this paper, we studied a motion estimator(ME) for H.264/AVC. The designed motion estimator is based on 2-D systolic array and it connects processing elements for fast SAD(Sum of Absolute Difference) calculation in parallel. By providing different path for the upper and lower lesion of each reference data and adjusting the input sequence, consecutive calculation for motion estimation is executed without pipeline stall. With data reuse technique, it reduces memory access, and there is no extra delay for finding optimal partitions and motion vectors. The motion estimator supports variable-block size and takes 328 cycles for macro-block calculation. The proposed architecture is local memory-free different from paper [6] using local memory. This motion estimation encoder can be applicable to real-time video processing.

• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.305-315
• /
• 2008

Pre-proposed AHHS(Adaptive Hierarchical Hexagon Search) is a kind of the fast hierarchical block matching algorithm based on the AHS(Adaptive Hexagon Search). It is characterized as keeping the merits of the AHS capable of fast estimating motion vectors and also adaptively reducing the local minima often occurred in the video sequences with higher spatio-temporal motion activity. The objective of this paper is to propose the method effectively extending the horizontal biased pattern and the vertical biased pattern of the AHHS to improve its predictive image quality. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive image quality and the computational time. The simulation results indicated that the proposed method was both suitable for (quasi-) stationary and large motion searches. While the proposed method increased the computational load on the process extending the hexagon search patterns, it could improve the predictive image quality so as to cancel out the increase of the computational load.

• Journal of Broadcast Engineering
• /
• v.16 no.5
• /
• pp.738-749
• /
• 2011

In this paper, we study QoS(Quality of Service) control protocols and the effect using MAC/PHY parameters of client device in mobile network. We proposes the way of controling the bit-rate by estimating the channel condition of the client with measured MAC/PHY parameters which is sent from the client. With the proposed method, more accurate available bit-rate can be estimated compared to conventional protocol, RTCP(Real-time Transport Control Protocol). The accurate bit-rate estimation can decrease wasted bit-rate and transport delay. In the result of the advantages, the transported video quality can be enhanced. In this paper, we show the effects of enhancement using client's the field data measured in WiMAX.

• The Journal of the Korea Contents Association
• /
• v.9 no.11
• /
• pp.18-26
• /
• 2009

Image resolution enhancement algorithm is a basic technique for image enlargement and restoration. The main problem is the image quality degradation such as blurring or blocking effects. In this paper, we propose loss information estimation and image resolution enhancement method using low level interpolation method. In the proposed method, loss information is computed by downsampling -interpolation process of obtained low resolution image. We estimate loss information of high resolution image using interpolation of the computed loss information. Lastly, we add up interpolated high resolution image and the estimated loss information which is applied a weight factor. Our experiments obtained the average PSNR 1.4dB which is improved results better than conventional algorithm. Also subjective image quality is more clearness and distinctness. The proposed method may be helpful for various video applications which required improvement of image.

• Journal of KIISE:Software and Applications
• /
• v.32 no.10
• /
• pp.949-955
• /
• 2005

In this Paper, we propose fast block matching algorithm by dividing complex areas based on complexity order of reference block and square sub-block to reduce an amount of computation of full starch(FS) algorithm for fast motion estimation, while keeping the same prediction quality compared with the full search algorithm. By using the fact that matching error is proportional to the gradient of reference block, we reduced unnecessary computations with square sub-block adaptive matching scan based image complexity instead of conventional sequential matching scan and row/column based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination(PDE) algorithm without any prediction quality, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Proceedings of the IEEK Conference
• /
• 2000.11d
• /
• pp.155-158
• /
• 2000

In this paper, the quantization noise in block-based video coding is analyzed, and a post-processing method based on the analysis is presented for reducing the quantization noise by using a wavelet transform(WT). In the proposed method, the quantization noise is considered as the sum of a blocking noise expressed as a deterministic profile and the random remainder noise. Each noise is removed in a viewpoint of image restoration using a 1-D WT, which yields a regularized differentiation. The blocking noise first is reduced by weakening the strength of each blocking noise component that appears as an impulse in the first scale wavelet domain. The impulse strength estimation is performed using median filter, quantization parameter(QP), and local activity. The remainder noise, which is considered as a white noise at non-edge pixels, then is reduced by soft-thresholding. The experimental results show that the proposed method yields better performance in terms if subjective quality as well as PSNR performance over VM post-filter in MPEG-4 for all test sequences of various compression ratios. We also present a fast post-processing in spatial domain equivalent to that in wavelet domain for real-time application.

• ETRI Journal
• /
• v.30 no.4
• /
• pp.506-515
• /
• 2008

The H.264/AVC standard has adopted new coding tools such as intra-prediction, variable block size, motion estimation with quarter-pixel-accuracy, loop filter, and so on. The adoption of these tools enables an H.264/AVC-coded bitstream to have more information than was possible with previous standards. In this paper, we propose an effective spatial error concealment method with low complexity in H.264/AVC intra-frame. From information included in an H.264/AVC-coded bitstream, we use prediction modes of intra-blocks to recover a damaged block. This is because the prediction direction in each prediction mode is highly correlated to the edge direction. We first estimate the edge direction of a damaged block using the prediction modes of the intra-blocks adjacent to a damaged block and classify the area inside the damaged block into edge and flat areas. Our method then recovers pixel values in the edge area using edge-directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show that the proposed method yields better video quality than conventional approaches.