Screen Content Hash Reuse for Faster Frame Coding
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Solution Overview
Problem
Existing screen content coding methods, such as intra block copy (IBC) and hash motion estimation (Hash ME), require calculating hash values for each pixel of each frame, leading to excessive computation and reduced processing efficiency due to redundant calculations.
Innovation Solution
Divide screen content into areas, detect pixel similarity between frames, reuse pixel hash tables for similar areas, and recalculate only for areas with significant changes, reducing redundant hash calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hash values are calculated for each pixel of each frame using existing IBC or Hash ME methods, then complete screen content coding is achieved, but computational complexity increases significantly and processing efficiency decreases
Solution Approach 1:
The patent divides the screen content into multiple areas and processes each area separately. By segmenting the full-frame hash calculation into area-based hash calculations, the computational complexity is reduced while maintaining coding completeness. Each area's hash table is built independently based on similarity detection with previous frames.
Solution Approach 2:
The patent applies different processing strategies to different areas based on their similarity to previous frames. Areas with high similarity reuse existing hash tables, while areas with low similarity undergo full hash recalculation. This local differentiation reduces overall computational complexity while ensuring reliable coding where needed.
2Manufacturing precision
If hash tables are rebuilt for every frame, then accurate screen content coding is achieved, but coding speed decreases due to redundant calculations
Solution Approach 1:
The patent performs preliminary similarity detection between current frame areas and previous frame areas before deciding whether to recalculate hash values. This preliminary action identifies areas that can reuse existing hash tables, avoiding redundant calculations and improving coding speed while maintaining accuracy where needed.
Solution Approach 2:
The patent changes the parameter of hash table update frequency based on area similarity. Instead of uniformly rebuilding hash tables for every frame, the system dynamically adjusts whether to recalculate hashes based on the similarity parameter, thereby improving coding speed without sacrificing accuracy in changed areas.
3Reliability
If the entire frame is processed using traditional methods, then comprehensive coding coverage is achieved, but processing time increases significantly
Solution Approach 1:
The patent segments the frame into multiple areas and processes them independently. This segmentation allows parallel processing of different areas and enables selective hash recalculation only for changed areas, reducing processing time while maintaining comprehensive coding coverage through systematic area-by-area processing.
Solution Approach 2:
The patent applies partial action by performing hash recalculation only for areas that have changed since the previous frame, rather than processing the entire frame uniformly. This selective approach reduces processing time significantly while maintaining coding coverage through similarity-based area identification.
Data Source
AI summary
A screen content processing method includes: dividing screen content into a plurality of areas; detecting pixel similarity between a first target area of a current frame of the screen content and a second target area of a previous frame of the screen content; using a pixel hash table of the second target area as a pixel hash table of the first target area if the similarity satisfies a first detection result; calculating pixel hash values of the first target area to establish a pixel hash table if the similarity satisfies a second detection result; traversing, according to a pixel hash table of an area to be coded in the first target area of the current frame, pixel hash tables of reference areas and performing intra block copy processing or hash motion estimation processing, to complete screen content processing for the first target area of the current frame.