Adaptive Global Motion Temporal Filtering for High Efficiency Video Coding

Krutz, Andreas; Glantz, Alexander; Tok, Michael; Esche, Marko; Sikora, Thomas

doi:10.1109/tcsvt.2012.2223012

Cited by 18 publications

(10 citation statements)

References 22 publications

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“…6 shows the comparison results for test 1 sequence of a city view with camera motion. The proposed algorithm shows better edges and textures than conventional H.264 and the method proposed in [6].…”

Section: Resultsmentioning

confidence: 90%

“…The proposed algorithm was compared with Krutz's algorithm [6] in terms of BD-PSNR and BD-rate [8]. Note Table 1 Global motion types of test sequences.…”

Section: Resultsmentioning

confidence: 99%

“…For temporal filtering, we employed Krutz's approach [6]. Krutz et al applied GMC to the coding loops in the decoder and encoder, and then performed block-based temporal filtering.…”

Section: Hole Fillingmentioning

confidence: 99%

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Prefiltering and Postfiltering Based on Global Motion Compensation for Improving Coding Efficiency in H.264 and HEVC Codecs

Ryu

Choi

Song

2017

IEICE Trans. Inf. & Syst.

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SUMMARYIn this paper, we propose a filtering approach based on global motion estimation (GME) and global motion compensation (GMC) for pre-and postprocessing of video codecs. For preprocessing a video codec, group of pictures (GOP), which is a basic unit for GMC, and reference frames are first defined for an input video sequence. Next, GME and GMC are sequentially performed for every frame in each GOP. Finally, a block-based adaptive temporal filter is applied between the GMC frames before video encoding. For postprocessing a video codec at the decoder end, every decoded frame is inversely motion-compensated using the transmitted global motion information. The holes generated during inverse motion compensation can be filled with the reference frames. The experimental results show that the proposed algorithm provides higher Bjontegaarddelta peak signal-to-noise ratios (BD-PSNRs) of 0.63 and 0.57 dB on an average compared with conventional H.264 and HEVC platforms, respectively.

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Section: Resultsmentioning

confidence: 90%

“…The proposed algorithm was compared with Krutz's algorithm [6] in terms of BD-PSNR and BD-rate [8]. Note Table 1 Global motion types of test sequences.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Prefiltering and Postfiltering Based on Global Motion Compensation for Improving Coding Efficiency in H.264 and HEVC Codecs

Ryu

Choi

Song

2017

IEICE Trans. Inf. & Syst.

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“…In recent years, several excellent GME algorithms [26][27][28][29][30] have been developed in an attempt to achieve both precision and computation. Okade et al [26] proposed the use of discrete wavelet transform in the block motion vector field to estimate the global motion parameters in the compressed domain.…”

Section: Related Workmentioning

confidence: 99%

“…Sung and Chung [29] presented a robust real-time camera motion estimation method that employs a fast detector with a multi-scale descriptor; the method entails minimal computation but exhibits high precision. Krutz et al [30] proposed the concept of global motion temporal filtering for the emerging video coding standard HEVC. All of these methods can be considered image-based GME.…”

Section: Related Workmentioning

confidence: 99%

Metadata-Assisted Global Motion Estimation for Medium-Altitude Unmanned Aerial Vehicle Video Applications

Li²,

Ding

et al. 2015

Remote Sensing

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Global motion estimation (GME) is a key technology in unmanned aerial vehicle remote sensing (UAVRS). However, when a UAV's motion and behavior change significantly or the image information is not rich, traditional image-based methods for GME often perform poorly. Introducing bottom metadata can improve precision in a large-scale motion condition and reduce the dependence on unreliable image information. GME is divided into coarse and residual GME through coordinate transformation and based on the study hypotheses. In coarse GME, an auxiliary image is built to convert image matching from a wide baseline condition to a narrow baseline one. In residual GME, a novel information and contrast feature detection algorithm is proposed for big-block matching to maximize the use of reliable image information and ensure that the contents of interest are well estimated. Additionally, an image motion monitor is designed to select the appropriate processing strategy by monitoring the motion scales of translation, rotation, and zoom. A medium-altitude UAV is employed to collect three types of large-scale motion datasets. Peak signal to noise ratio (PSNR) and motion scale are computed. This study's result is encouraging and applicable to other medium-or high-altitude UAVs with a similar system structure.

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