HEVC Video Coding Acceleration via Gradient Complexity and Adaboost
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video coding standards, such as H.264, fail to meet the compression requirements for high-definition and ultra-high-definition videos, necessitating a more efficient method for coding and decoding.
Innovation Solution
A method for accelerating HEVC video sequence coding and decoding is introduced, involving gradient calculations, block size division, and the use of an Adaboost classifier to determine prediction unit modes, reducing redundant calculations and optimizing coding units and prediction units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video coding standards (H.264) are used for high-definition and ultra-high-definition videos, then video quality can be maintained, but compression efficiency is insufficient and coding/decoding time is excessive
Solution Approach 1:
The video sequence is divided into multiple picture blocks that are processed independently. Each picture block undergoes separate gradient calculation, complexity assessment, and mode determination, enabling parallel processing and reducing overall coding time while maintaining compression efficiency.
Solution Approach 2:
Gradient calculations and complexity assessments are performed in advance during the decoding phase. The decoded picture blocks are pre-processed to compute gradient values and determine complexity metrics before the actual encoding process, which accelerates subsequent coding operations by having preparation work already completed.
2Measurement precision
If comprehensive gradient calculations are performed on all points in the LCU, then coding accuracy is improved, but computational complexity increases
Solution Approach 1:
Different regions of the picture block are treated differently based on their local characteristics. Gradient calculations are performed selectively - full calculations are done for regions with high complexity or important features, while simplified or skipped calculations are applied to low-complexity regions, optimizing the balance between accuracy and computational load.
Solution Approach 2:
The calculation precision is dynamically adjusted based on the complexity metric. For picture blocks with low complexity, simplified gradient calculations or pre-determined modes are used. For high-complexity blocks, full gradient calculations are performed. This adaptive parameter change reduces overall computational complexity while maintaining accuracy where needed.
3Manufacturing precision
If multiple candidate modes are evaluated for each prediction unit, then coding precision is improved, but processing time increases
Solution Approach 1:
Candidate modes are pre-sorted and ranked based on complexity metrics and gradient calculations performed during the decoding phase. The most promising modes are identified in advance, so that during encoding, only the top candidates need to be fully evaluated, significantly reducing the number of mode comparisons required while maintaining coding precision.
Solution Approach 2:
Instead of evaluating all possible candidate modes exhaustively, the method evaluates only a subset of the most promising modes based on preliminary complexity assessment. This partial evaluation approach achieves sufficient coding precision without the excessive time cost of complete mode exhaustion, particularly for low-complexity picture blocks where fewer modes need consideration.
Data Source
AI summary
Provided is a method for accelerating coding and decoding of an HEVC video sequence. The method includes following steps: an original video stream is decoded, a LCU and a PU1 are extracted, and the complexity of the PU1 is calculated; a block size division is performed; a quantization step QP1 of the original video stream is recorded; the decoded video stream is recoded, a quantization step QP2 of the recoded stream is set, and a CU2 of a previous frame of a frame to be coded and a CU3 of coded frames 1˜N−1 are extracted; a coding unit of a frame currently being coded is obtained; a final prediction unit mode is determined according to the PU1; a division mode of the coding unit of the frame currently being coded is determined according to a depth information category of the coding unit of the frame currently being coded.
