• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.843-846
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• 2000

An optical flow-based motion estimation algorithm is proposed for video coding. The algorithm uses block-matching motion estimation with an adaptive search region. The search region is computed from motion fields that are estimated based on the optical flow. The algorithm is based on the fact that true block-motion vectors have similar characteristics to optical flow vectors. Thereafter, the search region is computed using these optical flow vectors that include spatial relationships. In conventional block matching, the search region is fixed. In contrast, in the new method, the appropriate size and location of the search region are both decided by the proposed algorithm. The results obtained using test images show that the proposed algorithm can produce a significant improvement compared with previous block-matching algorithms.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.32-40
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• 1999

In this paper, we present a fast block matching motion estimation algorithm based on successive elimination algorithm (SEA). Based on the characteristic of center-biased motion vector distribution in the search area, the proposed method improves the performance of the SEA with a reduced the number of the search positions in the search area, In addition, to reduce the computational load, this method is combined with both the reduced bits mean absolute difference (RBMAD) matching criterion which can be reduced the computation complexity of pixel comparison in the block matching and pixel decimation technique which reduce the number of pixels used in block matching. Simulation results show that the proposed method provides better performance than existing fast algorithms and similar to full-search block motion estimation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.121-128
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• 2003

In this paper, we propose a new disparity estimation method called object based block matching algorithm(OBMA) for stereoscopic images which is able to reduce the blocking artifact. In the proposed algorithm, edge information of the given image is first extracted and then we estimate the disparity of each segmented object to remove the blocking artifact. In the experimental results, it is proven that the proposed algorithm has about the same performance as the old BMA algorithm while it achieves much better subjective quality.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1-4
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• 1996

It is difficult that a non-translational motion in a block is estimated by the block matching algorithm (BMA). In this paper, a nodal-displacement-based deformation model is used for this reason. This model assumes that a selected number of control nodes move freely in a block and that displacement of any interior point can be interpolated from nodal displacements. As a special case with a single node this model is equivalent to a translational model. And this model can represent more complex deformation using more nodes. We used an iterative gradient based search algorithm to estimate nodal displacement. Each iteration involves the solution of a simple linear equation. This method is called the deformable block matching algorithm (DBMA).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.313-325
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• 1996

This paper presents a new architecture for full-search block-matching motion estimation. The architecture is based on linear systolic arrays. High speed operation is obtained by feeding reference data, search data, and control signals into the linear systolic array in a pipelined fashion. Input data are fed into the linear systolic array at a half of the processor speed, reducing the required data bandwidth to half. The proposed architecture has a good scalability with respect to the number of processors and input bandwidth when the size of reference block and search range change.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.68-73
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• 2016

An efficient texture compression method is proposed based on a block matching process between the current block and the previously encoded blocks. Texture mapping is widely used to improve the quality of rendering results in real-time applications. For fast texture mapping, it is important to find an optimal trade-off between compression efficiency and computational complexity. Low-complexity methods (e.g., ETC1 and DXT1) have often been adopted in real-time rendering applications because conventional compression methods (e.g., JPEG) achieve a high compression ratio at the cost of high complexity. We propose a block matching-based compression method that can achieve a higher compression ratio than ETC1 and DXT1 while maintaining computational complexity lower than that of JPEG. Through a comparison between the proposed method and existing compression methods, we confirm our expectations on the performance of the proposed method.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.557-564
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• 2001

In general, several moving regions with different motions coexist in a block located on motion boundaries in the block-based motion estimation. In this case the motion compensation error(MCEs) are different with the moving regions. This is inclined to deteriorate the quality of motion compensated images because of the inaccurate motions estimated from the conventional mean absolute error(MAE) based matching function in which the matching error per pixel is accumulate throughout the block. In this paper, we divided a block into the regions according to their motions using the motion information of the spatio-temporally neighboring blocks and calculate the average MCF for each moving mentioned. From the simulation results, we showed the improved performance of the proposed method by comparing the results from other methods such as the full search method and the edge oriented block matching algorithm. Especially, we improved the quality of the motion compensated images of blocks on motion boundaries.

• Journal of Information Technology Services
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• v.2 no.2
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• pp.111-119
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• 2003

In this paper, an efficient block matching algorithm which is based on the Block Sum Pyramid Algorithm (BSPA) is presented. The cost of BSPA[1] was reduced in the proposed algorithm by using l2 norm and partial distortion elimination technique. Motion estimation accuracy of the proposed algorithm is equal to that of BSPA. The efficiency of the proposed algorithm was verified by experimental results.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.167-169
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• 2005

The occurrence of a single bit error in transmission bitstream leads to serious temporal and spatial errors. Because moving picture coding as MPEG-2 based on block coding algorithm uses variable length coding and motion compensation coding algorithm. In this paper, we propose algorithm to conceal occurred error of I-frames in transmission channel using data of the neighboring blocks in decoder. We divide a damaged macroblock of I-frame into four sub blocks and compose new macroblock using the neighboring blocks for each sub block. We estimate the block with minimum difference value through block matching with previous frame for new macroblocks and replace each estimated block with damaged sub block in the same position. Through simulation results, the proposed algorithm will be applied to a characteristic of moving with effect and shows better performance than conventional error concealment algorithms from visual and PSNR of view.

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