• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.161-163
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• 2005

In this paper, we propose an efficient motion vector recovery algorithm for the new coding standard H.264, which makes use of the Lagrange interpolation formula. In H.264/AVC, a 16$\times$16 macroblock can be divided into different block shapes for motion estimation, and each block has its own motion vector. In the natural video the motion vector is likely to move in the same direction, hence the neighboring motion vectors are correlative. Because the motion vector in H.264 covers smaller area than previous coding standards, the correlation between neighboring motion vectors increases. We can use the Lagrange interpolation formula to constitute a polynomial that describes the motion tendency of motion vectors, and use this polynomial to recover the lost motion vector. The simulation result shows that our algorithm can efficiently improve the visual quality of the corrupted video.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.68-74
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• 1998

Block-based interframe interpolation algorithms cause severe block effect because the algorithm interpolates the skipped frame by using block based motion vector. Therefore, in this paper, we propose an algorithm that reduces the block effect in the interpolated frames. First, we propose an algorithm that obtains backward motion vector by using forward motion vector received from the transmitter. In order to predict well covered and uncovered region, backward motion vector is needed as well as forward motion vector. Second, we propose the algorithm which segments the motion boundary blocks into regions and obtains the motion vector of each region from candidates that consist of the motion vectors of neighbor blocks. This algorithm makes it possible that the moving object and the background, in spite of being in the same block, have different motion vectors from each other so that the block effect can be reduced. According to the results of simulation, the proposed algorithm is superior to conventional algorithm in subjective quality a swell as in objective quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7C
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• pp.687-696
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• 2009

The motion compensated interpolation method is widely used to increase video frame rates. Especially, the bilateral motion estimation technique provides the improved results, since it doesn't make the overlapping and missing blocks in the interpolated frame. However, the motion vectors, which are obtained by the bilateral motion estimation, sometimes require further correction. In this paper, we propose the efficient motion vector.correction method for the bilateral motion estimation technique. By comparing the motion vectors of neighboring blocks and searching the new motion vector after merging the neighboring blocks, the erroneous motion vectors are efficiently corrected. It is shown that the proposed method provides better results, compared with the conventional methods.

• ETRI Journal
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• v.33 no.2
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• pp.295-298
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• 2011

We propose a motion-compensated frame interpolation method in which an accurate backward/forward motion vector pair (MVP) is estimated based on a parabolic motion model. A reliability measure for an MVP is also proposed to select the most reliable MVP for each interpolated block. The possibility of deformation of bidirectional corresponding blocks is estimated from the selected MVP. Then, each interpolated block is produced by combining corresponding blocks with the weights based on the possibility of deformation. Experimental results show that the proposed method improves PSNR performance by up to 2.8 dB as compared to conventional methods and achieves higher visual quality without annoying blockiness artifacts.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.275-282
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• 2004

In this paper, a transcoding method that transforms MPEG-4 video bitstream coded in 30 Hz frame rate into H.264 video bitstream of 15 Hz frame rate is proposed. The block modes and motion vectors in MPEG-4 is utilized in H.264 for block mode conversion and motion vector (MV) interpolation methods. The proposed three types of MV interpolation method can be used without performing full motion estimation in H.264. The proposed transcoder reduces computation amount for full motion estimation in H.264 and provides good quality of H.264 video at low bitrates. In experimental results, the proposed methods achieves 3.2-4 times improvement in computational complexity compared to the cascaded pixel-domain transcoding, while the PSNR (peak signal to noise ratio) is degraded with 0.2-0.9dB depending on video sizes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.123-131
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• 2009

The emerging display technology has been replaced the previous position of the CRT with the LCD. The nature of hold type display such as LCD, however, causes many problems such as motion blur and motion judder. To resolve the problems, we used frame interpolation technique which improves the image quality by inserting new interpolated frames between existing frames. In this paper, we propose a novel frame interpolation technique that uses dominant MV and variance different value in each block. At first, the proposed algorithm performs unidirectional motion estimation using blocking matching algorithm. The new frame is generated by pixel average using compared block variance or by pixel motion compensation using dominant motion vector, whether the motion estimation find the target area or not. Several experiments with the proposed algorithm shows that the proposed algorithm has better image quality than the existing bidirectional frame interpolation algorithm at the rate of about 3dB PSNR and has low complexity comparing to the unidirectional frame interpolation technique.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.265-272
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• 2015

A new technology on video frame rate up-conversion (FRUC) is presented by combining the median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to have a motion vector. Then, the OD method is used to refine motion vector in the occlusion region. Since the wrong motion vector can be obtained with high possibility in the occluded area, a median filtering that less depends on the motion vector is applied to that area, and since the motion vector is continuous and robust in the non-occluded area, BDMC(Bi-Directional Motion Compensated interpolation) is applied to obtain interpolated image in that area. BDMC using the bi-directional motion vectors achieves good results when continuity and robustness of the motion vector is higher. Experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain of PSNR (Peak Signal to Noise Ratio) is approximately 0.16 dB in the test sequences compared with BDMC.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.40-47
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• 2003

In this paper, we propose a new method for reducing the computational overhead of fine-to-coarse multi-resolution motion estimation (MRME) at the finest resolution level by searching for the region to consider motion vectors of the coarsest resolution subband. At this time, if half-pel accuracy motion estimation (HPAME) is used in the baseband where influence a lot of effect to the reconstructed image, we can have the motion vector exactly But, this method causes to higher computational overhead. So we suggest the method to the computational overhead by using selective interpolation. Experimental results show that the proposed algorithm gives better results than the traditional algorithms from image quality.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.54-63
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• 2004

A new motion compensated frame Interpolation (MCI) algorithm by block based motion estimation (BME) is proposed. The block for the BME is composed of a large overlapped block for practical object motion estimation (ME) and a small block (which has a coinciding center with the ME-block) for the more precise motion compensated image description. Pixels in the block for the ME are sub-sampled to reduce computational complexity. The proposed method is executed with the various ME-blocks which have different size and sub-sampling ratio, and compared to the conventional method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.130-140
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• 1998

This paper presents a method to estimate subpixel accuracy motion vectors using a mathermatical model withoug interpolation. the proposed method decides the coefficients of mathematical model, which represents the motion vector which is achieved by full search. And then the proposed method estimates subpixel accuracy motion vector from achieved mathematical model. Step by step mathematical models such as type 1, type 2, type 3, modified bype 2, modified type 3, and Partial Interpolation type 3 are presented. In type 1, quadratic polynomial, which has 9 unknown coefficients and models the 3by 3 pixel plane, is used to get the subpixel accuracy motion vectors by inverse matrix solution. In type 2 and 3, each quadratic polynomial which is simplified from type 1 has 5 and 6 unknown coefficients and is used by least square solution. Modified type 2 and modified type 3 are enhanced models by weighting only 5 pixels out of 9. P.I. type 3 is more accurate method by partial interpolation around subpixel which isachieved by type 3. LThese simulation results show that the more delicate model has the better performance and modified models which are simplified have excellent performance with reduced computational complexity.