Sparse Matrix Motion Vectors for Lossless Remote Desktop Compression
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Solution Overview
Problem
Existing video compression techniques, such as block-based lossy motion compensation, are unsuitable for computer-rendered images like remote desktops due to excessive distortion and high processing intensity, which compromises user experience and is not efficient for software implementations.
Innovation Solution
A method and apparatus for content-independent lossless motion determination using sparse matrices, where a host computer generates hash values for changed pixels, overwrites (X, Y) information in a symbol table, and transmits motion vectors to a client computer, efficiently determining pixel areas and reducing processing demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If block-based lossy motion compensation is used, then processing efficiency is improved, but image quality deteriorates due to excessive distortion
Solution Approach 1:
The patent segments the image into macroblocks and further divides them into 4x4 pixel groups. This hierarchical segmentation enables efficient processing at the macroblock level while maintaining lossless motion compensation at the pixel group level, resolving the contradiction between processing efficiency and image quality.
Solution Approach 2:
The patent applies different processing qualities to different regions: lossless motion compensation is applied to regions with computer-rendered content (text, icons) while allowing more flexibility in natural image regions. This local quality approach maintains high image quality where needed while preserving overall processing efficiency.
2Manufacturing precision
If visual anchor points are used for lossless motion compensation, then image quality is maintained, but processing intensity increases significantly
Solution Approach 1:
The patent extracts only the necessary information (pixel values at specific positions) from the macroblocks to form 4x4 pixel groups for motion compensation. This extraction approach avoids the intensive processing of searching for visual anchor points while maintaining the ability to perform lossless motion compensation.
Solution Approach 2:
The patent performs preliminary segmentation of macroblocks into 4x4 pixel groups before motion compensation. This preliminary organization enables more efficient processing during the motion estimation phase, reducing the overall processing intensity compared to anchor point methods.
3Manufacturing precision
If extensive identifiers are generated in reference image, then lossless motion vectors can be determined, but processing demands increase and hardware-based encoding is required
Solution Approach 1:
The patent uses simple 4x4 pixel group representations instead of extensive identifiers. These lightweight data structures can be processed efficiently by software without requiring hardware-based encoding, reducing device complexity while maintaining motion vector accuracy.
Data Source
AI summary
A method and apparatus for motion determination comprising generating a hash value for each changed pixel in a frame of an image display sequence, the changed pixels indicated in a set of sparse display coordinates, for each changed pixel, overwriting (X, Y) information at a position in a symbol table indexed by the hash value, the (X, Y) information comprising one display coordinate associated with the each changed pixel, generating motion vectors for a frame, each motion vector specifying a pixel area determined from at least one (X, Y) delta between one of the changed pixels represented in the symbol table and a previously changed pixel represented at the position in a previous frame symbol table for a previous frame in the image display sequence, and transmitting the motion vectors from the host computer over a network to a client computer.