Spatial Scalable Video Upsampling Filter Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video image compression technologies, specifically in H.264 standard, face high calculation complexity and poor coding performance due to the use of the same filters for both luminance and chrominance components during upsampling in spatial scalable coding, which is inefficient and not optimized for human visual sensitivity.
Innovation Solution
Adopting different filters for upsampling luminance and chrominance components, with simpler filters for chrominance to reduce calculation complexity while maintaining coding performance, such as using a 6-order filter for luminance and a 4- or 2-order filter for chrominance, based on the principle that human eyes are less sensitive to chrominance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the same filter is used for both luminance and chrominance components during upsampling, then the implementation is simple, but the calculation complexity is high and coding performance is poor
Solution Approach 1:
The patent applies different filter orders to different color components: a first filter order for luminance components and a second filter order for chrominance components. This local differentiation optimizes processing for each component's specific requirements, improving overall coding performance while maintaining implementation feasibility.
2Productivity
If a high-order filter is used for chrominance component, then the coding performance is improved, but the calculation complexity increases significantly
Solution Approach 1:
The patent changes the filter order parameter based on the color component type. By setting different filter orders (first order for luminance, second order for chrominance), the system optimizes the balance between coding performance and calculation complexity for each component according to human visual sensitivity characteristics.
3Productivity
If different filters with different orders are used for luminance and chrominance components, then the coding performance is improved and calculation complexity is reduced, but the device complexity increases
Solution Approach 1:
The patent segments the filtering process by component type, applying distinct filter orders to luminance and chrominance components separately. This segmentation allows optimized processing for each component while maintaining clear implementation boundaries through component-based classification.
Data Source
AI summary
The invention relates to video image compression technologies, and discloses a method and system for upsampling a spatial scalable coded video image so that during upsampling computation complexity may be reduced while coding performance is substantially unchanged. In the invention, the principle that human eyes are far less sensitive to a chrominance components than to a luminance components is utilized, and a simpler filter is adopted for the chrominance components than that for the luminance components during upsampling in I_BLINTRA_Base inter-layer prediction or residual samples image inter-layer prediction, thereby reducing effectively calculation complexity while coding performance is substantially unchanged.