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

Judging a video by its bitstream cover

Classifying videos into distinct categories, such as Sport and Music Video, is crucial for multimedia understanding and retrieval, especially in an age where an immense volume of video content is constantly being generated. Traditional methods require video decompression to extract pixel-level features like color, texture, and motion, thereby increasing computational and storage demands. Moreover, these methods often suffer from performance degradation in low-quality videos. We present a novel approach that examines only the post-compression bitstream of a video to perform classification, eliminating the need for bitstream. We validate our approach using a custom-built data set comprising over 29,000 YouTube video clips, totaling 6,000 hours and spanning 11 distinct categories. Our preliminary evaluations indicate precision, accuracy, and recall rates well over 80%. The algorithm operates approximately 15,000 times faster than real-time for 30fps videos, outperforming traditional Dynamic Time Warping (DTW) algorithm by six orders of magnitude

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

Substituent effects and mechanism elucidation of enantioselective sulfoxidation catalyzed by vanadium Schiff base complexes

The effects of substituents of the Schiff base ligands on oxo-vanadium-catalyzed enantioselective sulfoxidation were first systematically studied, and a rational mechanism of enantioselective sulfoxidation based on our experimental data and the reported data is proposed

Simultaneous Optimization of Structure and Operation for Coking Wastewater Biological Treatment Process

In this paper, the simultaneous optimization of process structure and operation conditions for the coking wastewater biological treatment process is carried out based on a superstructure-based model. The superstructure proposed covers current widely used biological treatment processes in a coking wastewater treatment plant. The activated sludge model no. 3 calibrated for coking wastewater and thickening factors is chosen to describe the biological processes and the secondary clarifier, respectively. The optimization problem is formulated as a mixed integer nonlinear programming model (MINLP), which is implemented and solved using the general algebraic modeling system (GAMS). For given influent coking wastewater flow rate and composition as input, the O/A/O process and A/O/O process are selected for the influent with COD concentration of 2000 and 3000 g/m(3) respectively. The results provide the valuable information for the development and operation of activated sludge processes for coking wastewater biological treatment and useful insights for policy makers as well