Screen Content Video Coding Reference Frame Management
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Solution Overview
Problem
Desktop sharing technologies face inefficiencies in screen content video coding due to the complexity of searching for suitable reference frames among multiple frames, especially with large frame resolutions and dynamic content like page switching and scrolling, which hampers compression efficiency.
Innovation Solution
The implementation of a hash or checksum function, such as MD5, to determine hash code values for partitioned portions of current frames, allowing for efficient comparison with reference frames to select candidate reference frames for coding, thereby optimizing reference frame management and improving inter-frame prediction compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple reference frames are used for screen content video coding, then compression efficiency is improved, but complexity of searching for the best match increases substantially
Solution Approach 1:
The patent divides the frame into multiple partitions or blocks, and computes hash values for each partition separately. This segmentation allows the search process to work with smaller, manageable units rather than entire frames, reducing the computational complexity while maintaining compression efficiency through partition-level matching.
Solution Approach 2:
The patent transforms the reference frame search problem from direct pixel comparison to hash value comparison. By changing the parameter from raw pixel data to computed hash codes, the system achieves faster matching with reduced computational complexity, enabling efficient search among multiple reference frames.
2Speed
If hash code comparison is used for reference frame selection, then coding speed is accelerated, but some precision in match detection may be lost
Solution Approach 1:
By partitioning the frame into multiple blocks and computing hash values for each partition, the system increases the granularity of comparison. This segmentation allows for more precise match detection at the partition level, reducing the risk of false positives while maintaining the speed benefits of hash-based comparison.
Solution Approach 2:
The patent performs hash comparison on multiple partitions rather than a single holistic hash. This partial action approach provides a more thorough and precise match detection by examining different regions independently, ensuring higher accuracy while maintaining computational efficiency through the use of hash functions.
Data Source
AI summary
Techniques are provided for reference frame management for screen content video coding using hash or checksum functions. A video data stream including a plurality of frames is received, each frame including a plurality of pixels that define content within the frame. A plurality of hash code values associated with partitioned portions of a current frame are determined, where each hash code value is determined as an output value from a hash or checksum function based upon an input value comprising pixel values for a corresponding partition within the current frame. The current frame is compared with a plurality of reference frames based upon a comparison of the hash code values of the current frame with hash code values of the reference frames. A reference frame is selected as a candidate reference frame for coding the current frame.