Pulse Vector Coding Using Statistical Models for Lower Video Bit Rate
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video signal encoding methods are inefficient, particularly for high-definition video, leading to increased bandwidth requirements and computational complexity, which is not adequately addressed by existing factorial pulse coding (FPC) methods designed for audio applications.
Innovation Solution
Adaptation of FPC for video encoding by incorporating statistical analysis and probability models to efficiently encode and decode pulse vectors, utilizing techniques like range coding, conditional arithmetic coding, and adaptive arithmetic coding to reduce bit rate while maintaining video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional video encoding methods are used, then video quality is maintained, but bandwidth requirements and computational complexity increase significantly for high-definition video
Solution Approach 1:
The video signal is divided into pulse vectors representing portions of video frames. Each pulse vector is encoded independently using statistical analysis, breaking down the complex video encoding task into manageable segments that can be processed efficiently
Solution Approach 2:
The patent applies factorial pulse coding to transform the encoding parameters from traditional pixel-based representation to pulse-based representation. By changing the fundamental parameter from pixel values to pulse vectors with statistical properties, the computational complexity is reduced while maintaining encoding effectiveness
2Reliability
If traditional video encoding methods are used, then video quality is maintained, but bandwidth requirements increase for high-definition video
Solution Approach 1:
The patent transforms the encoding approach by changing from pixel-based parameters to pulse vector parameters. This parameter transformation enables more compact representation of video data, reducing the quantity of data that needs to be transmitted while preserving visual quality
Solution Approach 2:
The patent performs preliminary statistical analysis on pulse vectors before encoding. By pre-processing the video data to identify statistical properties and patterns, the encoding process can achieve higher compression efficiency, reducing the bandwidth required for transmission
3Device complexity
If factorial pulse coding is applied to video, then computational complexity is reduced, but the method needs adaptation for video-specific requirements
Solution Approach 1:
The patent adapts factorial pulse coding by applying it locally to specific pulse vectors within the video frame structure. Rather than applying a uniform encoding method throughout, the solution tailors the encoding approach to the local statistical properties of different video regions, improving adaptability to various video content types
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.