291 research outputs found
Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications
Networked video applications, e.g., video conferencing, often suffer from
poor visual quality due to unexpected network fluctuation and limited
bandwidth. In this paper, we have developed a Quality Enhancement Network
(QENet) to reduce the video compression artifacts, leveraging the spatial and
temporal priors generated by respective multi-scale convolutions spatially and
warped temporal predictions in a recurrent fashion temporally. We have
integrated this QENet as a standard-alone post-processing subsystem to the High
Efficiency Video Coding (HEVC) compliant decoder. Experimental results show
that our QENet demonstrates the state-of-the-art performance against default
in-loop filters in HEVC and other deep learning based methods with noticeable
objective gains in Peak-Signal-to-Noise Ratio (PSNR) and subjective gains
visually
A Convolutional Neural Network Approach for Half-Pel Interpolation in Video Coding
Motion compensation is a fundamental technology in video coding to remove the
temporal redundancy between video frames. To further improve the coding
efficiency, sub-pel motion compensation has been utilized, which requires
interpolation of fractional samples. The video coding standards usually adopt
fixed interpolation filters that are derived from the signal processing theory.
However, as video signal is not stationary, the fixed interpolation filters may
turn out less efficient. Inspired by the great success of convolutional neural
network (CNN) in computer vision, we propose to design a CNN-based
interpolation filter (CNNIF) for video coding. Different from previous studies,
one difficulty for training CNNIF is the lack of ground-truth since the
fractional samples are actually not available. Our solution for this problem is
to derive the "ground-truth" of fractional samples by smoothing high-resolution
images, which is verified to be effective by the conducted experiments.
Compared to the fixed half-pel interpolation filter for luma in High Efficiency
Video Coding (HEVC), our proposed CNNIF achieves up to 3.2% and on average 0.9%
BD-rate reduction under low-delay P configuration.Comment: International Symposium on Circuits and Systems (ISCAS) 201
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