scholarly journals Low complexity in-loop prediction perceptual video coding for HEVC

2016 ◽  
Author(s):  
Y. G. Joshi ◽  
J. Loo ◽  
P. Shah ◽  
S. Rahman ◽  
A. Tasiran ◽  
...  
Keyword(s):  
Video Coding ◽  
Low Complexity ◽  
Loop Prediction ◽  
Perceptual Video Coding

scholarly journals Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Pengyu Liu ◽  
Kebin Jia
Keyword(s):  
Visual Perception ◽  
Video Coding ◽  
Saliency Detection ◽  
Motion Vector ◽  
Region Of Interest ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Characteristics Analysis ◽  
Perceptual Video Coding ◽  
Saliency Region

A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis. Firstly, this algorithm employs motion vector (MV) to extract temporal saliency region through fast MV noise filtering and translational MV checking procedure. Secondly, spatial saliency region is detected based on optimal prediction mode distributions in I-frame and P-frame. Then, it combines the spatiotemporal saliency detection results to define the video region of interest (VROI). The simulation results validate that the proposed algorithm can avoid a large amount of computation work in the visual perception characteristics analysis processing compared with other existing algorithms; it also has better performance in saliency detection for videos and can realize fast saliency detection. It can be used as a part of the video standard codec at medium-to-low bit-rates or combined with other algorithms in fast video coding.

scholarly journals Low-complexity motion-based saliency map estimation for perceptual video coding

CONATEL 2011 ◽  
2011 ◽  
Author(s):  
Ana Belen Mejia-Ocana ◽  
Manuel de-Frutos-Lopez ◽  
Sergio Sanz-Rodriguez ◽  
Oscar del-Ama-Esteban ◽  
Carmen Pelaez-Moreno ◽  
...  
Keyword(s):  
Video Coding ◽  
Low Complexity ◽  
Saliency Map ◽  
Map Estimation ◽  
Perceptual Video Coding

scholarly journals Low Complexity Trellis-Coded Quantization in Versatile Video Coding

2021 ◽  
Vol 30 ◽  
pp. 2378-2393
Author(s):  
Meng Wang ◽  
Shiqi Wang ◽  
Junru Li ◽  
Li Zhang ◽  
Yue Wang ◽  
...  
Keyword(s):  
Video Coding ◽  
Low Complexity ◽  
Trellis Coded

scholarly journals Low-complexity 8-point DCT approximation based on angle similarity for image and video coding

2018 ◽  
Vol 30 (3) ◽  
pp. 1363-1394 ◽  
Author(s):  
Raíza S. Oliveira ◽  
Renato J. Cintra ◽  
Fábio M. Bayer ◽  
Thiago L. T. da Silveira ◽  
Arjuna Madanayake ◽  
...  
Keyword(s):  
Video Coding ◽  
Low Complexity ◽  
Dct Approximation

scholarly journals Video Compression for Screen Recorded Sequences Following Eye Movements

2021 ◽  
Author(s):  
Diego Jesus Serrano-Carrasco ◽  
Antonio Jesus Diaz-Honrubia ◽  
Pedro Cuenca
Keyword(s):  
Eye Tracking ◽  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
High Efficiency ◽  
Tracking System ◽  
Bit Rate ◽  
Video Traffic ◽  
High Efficiency Video Coding ◽  
Perceptual Video Coding

AbstractWith the advent of smartphones and tablets, video traffic on the Internet has increased enormously. With this in mind, in 2013 the High Efficiency Video Coding (HEVC) standard was released with the aim of reducing the bit rate (at the same quality) by 50% with respect to its predecessor. However, new contents with greater resolutions and requirements appear every day, making it necessary to further reduce the bit rate. Perceptual video coding has recently been recognized as a promising approach to achieving high-performance video compression and eye tracking data can be used to create and verify these models. In this paper, we present a new algorithm for the bit rate reduction of screen recorded sequences based on the visual perception of videos. An eye tracking system is used during the recording to locate the fixation point of the viewer. Then, the area around that point is encoded with the base quantization parameter (QP) value, which increases when moving away from it. The results show that up to 31.3% of the bit rate may be saved when compared with the original HEVC-encoded sequence, without a significant impact on the perceived quality.

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