Video Residual Processing for Adaptive Compression and Fidelity
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Solution Overview
Problem
Existing video coding technologies struggle to efficiently compress diverse video content types, such as high-speed motion and static elements, while maintaining low complexity and high fidelity, as different features often require different compression approaches.
Innovation Solution
A method of encoding video signals by generating and modifying residual data sets based on differences between input and reconstructed signals, using selective encoding and transformation to reduce data size and computational complexity, while preserving viewer experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional video coding compression approaches are applied to diverse video content types, then data size is reduced, but compression effectiveness deteriorates because different feature types (high-speed motion, static elements) require different compression approaches
Solution Approach 1:
The patent segments the video coding process into separate handling of different feature types. It processes high-speed motion regions and static elements (text, logos) through different compression paths, allowing each segment to be optimized for its specific characteristics rather than applying a uniform compression approach to the entire video stream.
Solution Approach 2:
The patent applies local quality by adapting compression parameters and methods to different spatial and temporal regions of the video. Static elements receive different processing than dynamic motion regions, with each area receiving the quality and compression intensity appropriate to its nature, thereby improving overall compression effectiveness.
2Manufacturing precision
If enhanced video coding processing is applied to improve fidelity, then reconstruction quality is improved, but processing complexity and computational load increase
Solution Approach 1:
The patent segments the processing complexity by handling different video regions separately. Computationally intensive processing is applied only where necessary (e.g., to static elements that require high fidelity), while simpler processing is applied to regions where less computational burden is needed, thus managing overall processing complexity.
Solution Approach 2:
The patent applies partial processing by providing enhanced fidelity processing only to the extent necessary for specific content types and regions. Rather than applying maximum processing uniformly across the entire video stream, it applies processing selectively to where it is most needed, balancing quality improvement with computational efficiency.
Data Source
AI summary
According to aspects of the invention there is provided a method of modifying sets of residuals data where residual data can be used to correct or enhance data of a base stream, for example a frame of a video encoded using a legacy video coding technology. According to a first aspect there is provided a method of encoding an input video, the method comprising: receiving an input video comprising a plurality of frames; generating one or more sets of residuals on a frame-by-frame basis based on a difference between a given frame of the input signal and one or more reconstructed versions of the given frame at one or more respective spatial resolutions; selectively modifying the one or more sets of residuals; and encoding the one or more sets of modified residuals to generate one or more respective encoded streams for the input video, wherein the method further comprises: determining a sum of absolute differences pixel metric based on one or more of the plurality of frames, the pixel metric being determined for one or more coding units of the one or more of the plurality of frames; and wherein the one or more sets of residuals are selectively modified based on the pixel metric.