5 research outputs found
Convex Optimization Based Bit Allocation for Light Field Compression under Weighting and Consistency Constraints
Compared with conventional image and video, light field images introduce the
weight channel, as well as the visual consistency of rendered view, information
that has to be taken into account when compressing the pseudo-temporal-sequence
(PTS) created from light field images. In this paper, we propose a novel frame
level bit allocation framework for PTS coding. A joint model that measures
weighted distortion and visual consistency, combined with an iterative encoding
system, yields the optimal bit allocation for each frame by solving a convex
optimization problem. Experimental results show that the proposed framework is
effective in producing desired distortion distribution based on weights, and
achieves up to 24.7% BD-rate reduction comparing to the default rate control
algorithm.Comment: published in IEEE Data Compression Conference, 201
A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding
Due to differences in frame structure, existing multi-rate video encoding
algorithms cannot be directly adapted to encoders utilizing special reference
frames such as AV1 without introducing substantial rate-distortion loss. To
tackle this problem, we propose a novel bayesian block structure inference
model inspired by a modification to an HEVC-based algorithm. It estimates the
posterior probabilistic distributions of block partitioning, and adapts early
terminations in the RDO procedure accordingly. Experimental results show that
the proposed method provides flexibility for controlling the tradeoff between
speed and coding efficiency, and can achieve an average time saving of 36.1%
(up to 50.6%) with negligible bitrate cost.Comment: published in IEEE Data Compression Conference, 201