• Journal of Information Display
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• v.5 no.3
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• pp.1-7
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• 2004

We developed a novel frame interpolation method to interpolate a frame between two successive original frames. Using this method, we are able to apply a double-rate driving method instead of an impulse driving method where a black frame is inserted between two successive original frames. The double-rate driving method enables amelioration of the motion blur of LCDs caused by the characteristics of human vision without reducing the luminosity of the whole screen. The image quality of the double-rate driving method was also found to be better than that of an impulse driving method using our motion picture simulator and an actual panel. Our initial model of our frame interpolation method consists of motion estimation with a maximum matching pixel count estimation function, an area segmentation technique, and motion compensation with variable segmentation threshold. Although salt and pepper noise remained in a portion of an object mainly due to inaccuracy of motion estimation, we verified the validity of our method and the possibility of improvement in hold-type motion blurring.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.251-254
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• 2004

We developed a novel Fame interpolation method to interpolate a frame between two successive original frames. Using this method, we are able to apply a double-rate driving method instead of an impulse driving method where a black Fame is inserted between two successive original Fames. The double-rate driving method enables improvement to the motion blur of LCDs caused by the characteristics of human vision without reducing the luminosity of the whole screen. Here, we report on the initial model of our frame interpolation method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.734-740
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• 2017

A frame rate up-conversion scheme is needed when moving pictures with a low frame rate is played on appliances with a high frame rate. Frame rate up-conversion methods interpolate the frame with two consecutive frames of the original source. This can be divided into the frame repetition method and motion estimation-based the frame interpolation one. Frame repetition has very low complexity, but it can yield jerky artifacts. The interpolation method based on a motion estimation and compensation can be divided into pixel or block interpolation methods. In the case of pixel interpolation, the interpolated frame was classified into four areas, which were interpolated using different methods. The block interpolation method has relatively low complexity, but it can yield blocking artifacts. The proposed method is the frame rate up-conversion method based on a block motion estimation and compensation using the linearity of motion. This method uses two previous frames and one next frame for motion estimation and compensation. The simulation results show that the proposed algorithm effectively enhances the objective quality, particularly in a high resolution image. In addition, the proposed method has similar or higher subjective quality than other conventional approaches.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.54-57
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• 2000

In this paper, we propose a new interpolation method by using the motion between two moving image frames. In the proposed method, the movement is detected by using neighborhood pixels of target pixel in the past frame and the present frame. Then, H-shaped pseudomedian filter (below HPMED) is used for the still part of the image and Delta-shaped interpolation filter (below $\Delta$-shaped) for used in the moving part of the image. We detect the movement by comparing the differences between pixels in 4${\times}$5 window of the past frame and the present frame; the difference has a critical value. We simultaneously accomplish checking PSNR(peak signal noise ratio) and subjective assessment that is placed the focus on edge characteristic for assessment of result in computer simulation. The results show that the proposed adaptive method is better than the conventional methods.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.201-206
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• 2011

FRUC (Frame Rate Up-Conversion) technique needs an effective frame interpolation algorithm using motion information between adjacent neighboring frames. In order to have good visual qualities in the interpolated frames, it is necessary to develop an effective detection and interpolation algorithms for occluded regions. For this aim, this paper proposes an effective occluded region detection algorithm through the adaptive forward and backward motion searches and also by introducing the minimum value of normalized cross-correlation coefficient (NCCC). That is, the proposed scheme looks for the location with the minimum sum of absolute differences (SAD) and this value is compared to that of the location with the maximum value of NCCC based on the statistics of those relations. And, these results are compared with the size of motion vector and then the proposed algorithm decides whether the given block is the occluded region or not. Furthermore, once the occluded regions are classified, then this paper proposes an adaptive interpolation algorithm for occluded regions, which still exist in the merged frame, by using the neighboring pixel information and the available data in the occluded block. Computer simulations show that the proposed algorithm can effectively classify the occluded region, compared to the conventional SAD-based method and the performance of the proposed interpolation algorithm has better PSNR than the conventional algorithms.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.927-928
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• 2008

In this paper, a interpolation error concealment algorithm of motion compensated interpolated frame for motion compensated frame rate conversion to reduce the block artifacts caused by failure of conventional motion estimation based on block matching algorithm is proposed. Experimental results show good performance of the proposed scheme with significant reduction of the block artifacts.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.537-543
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• 2015

Liquid crystal displays (LCDs) have slow responses, so motion blurs are often perceived in fast moving scenes. To reduce this motion blur, we propose a novel method of robust motion compensated frame interpolation (MCFI) based on bidirectional motion estimation (BME) and weight-overlapped block motion compensation (WOBMC) with variable block sizes. In most MCFI methods, a static block size is used, so some block artefacts and motion blurs are observed. However, the proposed method adjusts motion block sizes and search ranges by comparing matching scores, so the precise motion vectors can be estimated in accordance with motions. In the MCFI, overlapping ranges for WOBMC are also determined by adjusted block sizes, so the accurate MCFI can be performed. In the experimental results, the proposed method strongly reduced motion blurs arisen from large motions, and yielded interpolated images with high visual performance and peak signal-to-noise ratio (PSNR).

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.17-27
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• 2024

Video frame interpolation is an important technique used in the field of video and media, as it increases the continuity of motion and enables smooth playback of videos. In the study of video frame interpolation using deep learning, Kernel Based Method captures local changes well, but has limitations in handling global changes. In this paper, we propose a new U-Net structure that applies feature map differentiation and two directions to focus on capturing major changes to generate intermediate frames more accurately while reducing the number of parameters. Experimental results show that the proposed structure outperforms the existing model by up to 0.3 in PSNR with about 61% fewer parameters on common datasets such as Vimeo, Middle-burry, and a new YouTube dataset. Code is available at https://github.com/Go-MinSeong/SF-AdaCoF.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.1-8
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• 2012

Video FRUC (Frame Rate Up Conversion) has been a technique of great interest due to its diversified applications in consumer electronics. Most advanced FRUC algorithms adopt a motion interpolation technique to determine the motion vector field of interpolated frames. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame is reconstructed. For this aim, this paper proposes a distortion estimation for motion compensated interpolation frame using frame-adaptive distortion estimation. The proposed method is applied for the symmetric motion estimation and compensated scheme and then analyzed by three different approaches, that is, forward estimation, backward estimation and adaptive bi-directional estimation schemes. Through computer simulations, it is shown that the proposed bi-directional estimation method outperforms others and can be effectively applied for FRUC.