• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.880-887
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• 2015

In this paper, frame rate up conversion (FRUC) algorithm considering the direction and magnitude of identical motion vectors is proposed. extended bilateral motion estimation (EBME) has higher complexity than bilateral motion estimation (BME). By using average magnitude of motion vector with x and y direction respectively, dynamic frame and static frame are decided. We reduce complexity to decide EBME. also, After we compare the direction and magnitude of identical motion vectors, We reduce complexity to decide motion vector smoothing(MVS). Experimental results show that this proposed algorithm has fast computation and better peak singnal to noise ratio(PSNR) results compared with EBME.

• 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.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.342-348
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• 2013

In this paper, a novel frame rate up conversion (FRUC) algorithm using adaptive extended bilateral motion estimation (AEBME) is proposed. Conventionally, extended bilateral motion estimation (EBME) conducts dual motion estimation (ME) processes on the same region, therefore involves high complexity. However, in this proposed scheme, a novel block type matching procedure is suggested to accelerate the ME procedure. We calculate the edge information using sobel mask, and the calculated edge information is used in block type matching procedure. Based on the block type matching, decision will be made whether to use EBME. Motion vector smoothing (MVS) is adopted to detect outliers and correct outliers in the motion vector field. Finally, overlapped block motion compensation (OBMC) and motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which OBMC is employed adaptively based on frame motion activity. Experimental results show that this proposed algorithm has outstanding performance and fast computation comparing with EBME.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.797-805
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• 2014

In this paper we propose a new frame rate up conversion scheme which is used to overcome the motion blur problem of liquid crystal display caused by its slow response. The conventional bilateral motion estimation method which is mainly used in the frame rate up conversion scheme has a drawback that it cannot find true motion vector if there are blocks with simple texture in the search range. To solve this problem, a texture adaptive bilateral motion estimation method that increases cost value of block with simple texture is proposed. Also a motion estimation scheme that utilizes neighboring motion vector effectively is proposed to reduce computation time required to estimate motion. Since the proposed scheme does not apply all available motion vectors within the search range, the execution time of frame rate up conversion can be reduced dramatically. Experimental results show that the interpolated frame image quality of the proposed method is improved in subjective as well as objective view point compared with that of the conventional method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.62-69
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• 2015

In this paper, a new frame rate up conversion (FRUC) algorithm using adaptive motion estimation (AME-FRUC) is proposed. The proposed algorithm performs extended bilateral motion estimation (EBME) conducts motion estimation (ME) processes on the static region, and extract region of interest with the motion vector (MV). In the region of interest block, the proposed AME-FRUC uses the texture block partitioning scheme and the unilateral motion estimation for improving ME accuracy. Finally, motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which MCFI is employed adaptively based on ME scheme. Experimental results show that the proposed algorithm improves the PSNR up to 3dB, the SSIM up to 0.07 and 68% lower SAD calculations compared to the EBME and the conventional FRUC algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.135-142
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• 2009

Since hold-type display systems have been developed, frame-rate up conversion (FRUC) is an essential technique to improve the temporal resolution in the display. FRUC improves the temporal resolution by interpolating one or multiple intermediate frames between two adjacent frames. In this paper, a new frame-rate up-conversion algorithm based on bilateral motion refinement with rotation is proposed. First, we perform bi-directional motion estimation between adjacent two frames to obtain a motion vector for each block. Then, we apply a modified median filtering to motion vectors for outlier-rejection and motion field smoothing. The filtered motion vectors are updated by the bilateral motion refinement with rotation. After the refined motion vector is obtained, the intermediate frame is generated by applying the overlapped block motion compensation (OBMC). Experimental results show that the proposed algorithm provides a better performance than the previous methods subjectively and objectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.68-71
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• 2014

본 논문은 EBME(Extended Bilateral Motion Estimation)알고리듬에서 가중치수를 개선시켜 알고리듬을 제안하였다. 제안된 알고리듬은 EBME(Extended Bilateral Motion Estimation) MCI(Motion Compensated Interpolation)에서 고정된 확장블록을 대신하여 확장블록이 주변근처를 이동하면서 SOAD(Sum of Overlapped area Absolute Difference)를 통하여 향상된 가중치수를 찾는 알고리듬이다. 이 논문은 EBME알고리듬에 비해 PSNR(Peak Signal to Noise Ratio)이 향상된 성능을 보였다.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1048-1060
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• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.785-790
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• 2019

In this paper, a new bilateral frame rate up-conversion algorithm using adaptive overlapped block motion compensation is proposed. In this algorithm, the adaptive overlapped block motion compensation is based on the motion complexity of the reference region. As the motion complexity is determined by the size of the previously coded motion estimation prediction, the overlapped block motion compensation method is selected without any additional computational complexity. Experimental results show that the proposed algorithm provides better image quality than conventional methods both objectively and subjectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4170-4188
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• 2014

In this study, we present a denoising algorithm for high-frame-rate videos in an ultra-low illumination environment on the basis of Kalman filtering model and a new motion segmentation scheme. The Kalman filter removes temporal noise from signals by propagating error covariance statistics. Regarded as the process noise for imaging, motion is important in Kalman filtering. We propose a new motion estimation scheme that is suitable for serious noise. This scheme employs the small motion vector characteristic of high-frame-rate videos. Small changing patches are intentionally neglected because distinguishing details from large-scale noise is difficult and unimportant. Finally, a spatial bilateral filter is used to improve denoising capability in the motion area. Experiments are performed on videos with both synthetic and real noises. Results show that the proposed algorithm outperforms other state-of-the-art methods in both peak signal-to-noise ratio objective evaluation and visual quality.