Entropy Coding for Video Bitstreams With Adaptive Bin Buffers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently managing the bin-to-bit ratio during entropy encoding and decoding, leading to inefficient use of hardware resources and suboptimal compression efficiency as video sizes, resolutions, and frame rates increase.
Innovation Solution
The method involves restricting the bin-to-bit ratio by variably setting thresholds for entropy encoding and decoding, using adaptive entropy encoding/decoding methods for each basic unit, and efficiently operating a bin buffer to manage bitstream generation and parsing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video data is compressed using existing entropy encoding methods, then compression efficiency is improved, but hardware resource utilization becomes inefficient and bin buffer management becomes suboptimal
Solution Approach 1:
The patent implements dynamic bin buffer management where the bin buffer size and threshold values are adaptively adjusted based on the current encoding state, video content characteristics, and compression requirements. This allows the system to optimize hardware resource utilization in real-time rather than using fixed parameters, resolving the contradiction between compression efficiency and hardware resource efficiency.
Solution Approach 2:
The patent changes key parameters including bin buffer size, bin-to-bit ratio thresholds, and arithmetic coding precision levels adaptively during encoding. By modifying these parameters dynamically based on content complexity and compression targets, the system achieves optimal compression efficiency without excessive hardware resource consumption.
2Manufacturing precision
If video resolution and frame rate are increased, then image quality is improved, but the amount of data requiring encoding increases leading to inefficient compression
Solution Approach 1:
The patent applies different entropy encoding precision levels and bin buffer configurations to different regions or blocks within the video data. High-importance regions receive more precise encoding while less critical regions use coarser encoding, maintaining overall image quality while improving compression efficiency for high-resolution high-frame-rate content.
Solution Approach 2:
The patent uses adaptive precision control where full arithmetic coding precision is applied only when necessary based on content complexity, rather than uniformly across all data. This partial application of high-precision encoding maintains image quality for important regions while reducing computational burden for the overall high-volume data from high-resolution high-frame-rate video.
3Measurement precision
If bin buffer size is increased to improve encoding accuracy, then entropy encoding precision is improved, but memory usage increases and hardware resources are consumed
Solution Approach 1:
The patent implements dynamic bin buffer size adjustment where the buffer size is expanded only when the encoding content requires high precision (e.g., complex textures, high-frequency content) and contracted when encoding simpler content. This dynamic adaptation maintains encoding precision where needed while minimizing memory usage for the overall encoding process.
Solution Approach 2:
The patent changes the bin buffer size parameter adaptively based on content analysis and encoding progress. By modifying this parameter in response to actual encoding needs rather than using a fixed large buffer, the system achieves high entropy encoding precision when required while keeping average memory consumption lower.
Data Source
AI summary
A method is executed to efficiently operate a bin buffer to limit a bin-to-bit ratio in entropy encoding and decoding related to bitstream generation and parsing. In addition, a method of configuring a list includes various entropy encoding/decoding methods and adaptively uses the entropy encoding/decoding methods for each basic unit of entropy encoding/decoding.