An Efficient Motion-Compensated Frame Interpolation Method Using Temporal Information for High-Resolution Videos

2015 ◽  
Vol 11 (7) ◽  
pp. 580-588 ◽  
Author(s):  
DongYoon Kim ◽  
HyunWook Park
Keyword(s):  
High Resolution ◽  
Interpolation Method ◽  
Temporal Information ◽  
Frame Interpolation ◽  
Motion Compensated Frame Interpolation

scholarly journals A Fast 4K Video Frame Interpolation Using a Multi-Scale Optical Flow Reconstruction Network

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1251 ◽  
Author(s):  
Ahn ◽  
Jeong ◽  
Kim ◽  
Kwon ◽  
Yoo
Keyword(s):  
High Resolution ◽  
Optical Flow ◽  
State Of The Art ◽  
Interpolation Method ◽  
Video Frame ◽  
Frame Interpolation ◽  
Multi Scale ◽  
Reconstruction Scheme ◽  
Flow Reconstruction

Recently, video frame interpolation research developed with a convolutional neural network has shown remarkable results. However, these methods demand huge amounts of memory and run time for high-resolution videos, and are unable to process a 4K frame in a single pass. In this paper, we propose a fast 4K video frame interpolation method, based upon a multi-scale optical flow reconstruction scheme. The proposed method predicts low resolution bi-directional optical flow, and reconstructs it into high resolution. We also proposed consistency and multi-scale smoothness loss to enhance the quality of the predicted optical flow. Furthermore, we use adversarial loss to make the interpolated frame more seamless and natural. We demonstrated that the proposed method outperforms the existing state-of-the-art methods in quantitative evaluation, while it runs up to 4.39× faster than those methods for 4K videos.

scholarly journals Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

2017 ◽  
Vol 21 (4) ◽  
pp. 2187-2201 ◽  
Author(s):  
Pere Quintana-Seguí ◽  
Marco Turco ◽  
Sixto Herrera ◽  
Gonzalo Miguez-Macho
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Interpolation Method ◽  
Rain Gauge ◽  
Surface Model ◽  
Low Resolution ◽  
Precipitation Events

Abstract. Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980–2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

Detection of motion compensated frame interpolation via motion-aligned temporal difference

2018 ◽  
Vol 78 (6) ◽  
pp. 7453-7477 ◽  
Author(s):  
Xiangling Ding ◽  
Yue Li ◽  
Ming Xia ◽  
Jiale He ◽  
Gaobo Yang
Keyword(s):  
Temporal Difference ◽  
Frame Interpolation ◽  
Motion Compensated Frame Interpolation

scholarly journals The use of LIDAR as a data source for digital elevation models – a study of the relationship between the accuracy of digital elevation models and topographical attributes in northern peatlands

2011 ◽  
Vol 8 (3) ◽  
pp. 5497-5522 ◽  
Author(s):  
A. Hasan ◽  
P. Pilesjö ◽  
A. Persson
Keyword(s):  
High Resolution ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Drainage Area ◽  
Absolute Deviation ◽  
Weighting Method ◽  
Dem Resolution ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Topographical Attributes

Abstract. It is important to study the factors affecting estimates of wetness since wetness is crucial in climate change studies. The availability of digital elevation models (DEMs) generated with high resolution data is increasing, and their use is expanding. LIDAR earth elevation data have been used to create several DEMs with different resolutions, using various interpolation parameters, in order to compare the models with collected surface data. The aim is to study the accuracy of DEMs in relation to topographical attributes such as slope and drainage area, which are normally used to estimate the wetness in terms of topographic wetness indices. Evaluation points were chosen from the high-resolution LIDAR dataset at a maximum distance of 10 mm from the cell center for each DEM resolution studied, 0.5, 1, 5, 10, 30 and 90 m. The interpolation method used was inverse distance weighting method with four search radii: 1, 2, 5 and 10 m. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. The accuracy of the estimated elevation for different slopes was tested using the DEM with 0.5 m resolution. Drainage areas were investigated at three resolutions, with coinciding evaluation points. The ability of the model to generate the drainage area at each resolution was obtained by pairwise comparison of three data subsets. The results show that the accuracy of the elevations obtained with the DEM model are the same for different resolutions, but vary with search radius. The accuracy of the values (NMAD of errors) varies from 29.7 mm to 88.9 mm, being higher for flatter areas. It was also found that the accuracy of the drainage area is highly dependent on DEM resolution. Coarse resolution yielded larger estimates of the drainage area but lower slope values. This may lead to overestimation of wetness values when using a coarse resolution DEM.

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