Video Arithmetic Coding for Last Coefficient Position Encoding
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Solution Overview
Problem
Existing video encoding and decoding methods face challenges in balancing calculation complexity and compressive performance during entropy encoding and decoding of transformation coefficient information, particularly in combining high-complexity context-adaptive binary arithmetic coding (CABAC) with lower-complexity bypass arithmetic coding.
Innovation Solution
Classifying the location of the last significant coefficient into prefix and suffix bit strings based on a critical value, allowing for independent arithmetic encoding using CABAC for prefixes and bypass coding for suffixes to optimize processing speed and compressive performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If CABAC method is applied for encoding transformation coefficient symbols, then compressive performance is improved, but calculation complexity increases
Solution Approach 1:
The patent segments the transformation coefficient symbols into different types (significant coefficients, last significant coefficient position, non-significant coefficients) and applies different encoding methods to each segment. Specifically, it uses CABAC for significant coefficients to achieve high compression, while using simplified bypass coding for less critical data like non-significant coefficients, thus reducing overall calculation complexity while maintaining compressive performance.
Solution Approach 2:
The patent applies different encoding quality levels to different parts of the data based on their importance. High-priority data (significant coefficients) receive the more complex but more efficient CABAC encoding, while low-priority data (non-significant coefficients) use simpler bypass coding. This local differentiation optimizes the balance between compression efficiency and computational load.
2Device complexity
If bypass arithmetic coding method is applied, then calculation complexity is reduced, but compressive throughput decreases
Solution Approach 1:
The patent divides the encoding process into segments where bypass arithmetic coding is applied selectively to specific data types (non-significant coefficients and less critical syntax elements) rather than all data. This segmentation allows the system to use the computationally simpler bypass method where appropriate, reducing overall calculation complexity while maintaining adequate compression throughput for the entire bitstream.
3Loss of information
If high-complexity encoding methods are applied to all syntax elements, then compressive performance is maximized, but processing speed decreases
Solution Approach 1:
The patent segments syntax elements into categories based on their impact on compression efficiency and processes them using appropriate methods. Significant coefficients undergo detailed CABAC encoding to maximize compression, while non-significant coefficients use faster bypass coding. This segmentation enables the system to achieve high compressive performance for critical data while maintaining high processing speed through simplified encoding of less critical data.
Solution Approach 2:
The patent applies different encoding quality and speed characteristics to different parts of the data stream based on local requirements. Critical syntax elements receive high-quality CABAC encoding with thorough probability modeling, while non-critical elements use faster, lower-quality bypass encoding. This local quality adjustment optimizes the overall processing speed while maintaining compressive performance where it matters most.
Data Source
AI summary
Methods and apparatuses for arithmetic encoding/decoding of video data. The arithmetic decoding method includes arithmetically decoding prefix bit strings representing a two-dimensional location of a last significant coefficient in a block sequentially by using a context model, arithmetically decoding suffix bit strings in a bypass mode, and performing inverse binarization on the arithmetically decoded prefix bit strings and suffix bit strings to acquire the location of the last significant coefficient in the block.