Dynamic Warp Map Generation via Hypersurface Coefficients
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing electronic image warping technologies are inefficient in handling varying distortions, particularly in real-time applications, as they require extensive memory for storing multiple warp maps and are limited in flexibility and quality of output images due to restrictive hardware implementation and pixel-by-pixel descriptions.
Innovation Solution
A dynamic system that generates and stores compacted coefficients for hypersurface maps, allowing for efficient computation of warp maps based on user and control parameters, using a hybrid vector space divided into distortion control zones and geometry patches, enabling flexible and high-quality image transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple warp maps are stored in memory for different distortion parameters, then distortion compensation quality is improved, but memory resource requirements increase substantially
Solution Approach 1:
The patent segments the distortion parameter space into discrete levels (e.g., 3 levels of radial distortion, 3 levels of tangential distortion, 3 levels of keystone distortion). Instead of storing complete warp maps for all possible parameter combinations, the system stores only coefficient sets for each segment level, reducing memory requirements while maintaining compensation quality across the full parameter range.
Solution Approach 2:
The patent transforms the storage of complete warp maps into storage of parameter sets that define hypersurfaces. By changing from storing spatial coordinate mappings to storing mathematical parameters (coefficients) that generate these mappings dynamically, the system achieves the same distortion compensation quality with substantially reduced memory resources.
2Productivity
If a set of pre-determined warp maps is generated offline and stored, then hardware implementation efficiency is improved, but flexibility in handling varying distortions deteriorates
Solution Approach 1:
The patent introduces dynamics by enabling continuous adjustment of distortion parameters within predefined ranges. The system allows selective activation of different distortion levels (e.g., choosing between 3 levels of radial distortion) and combines them with user-defined parameters, creating a dynamic adaptation mechanism that maintains hardware efficiency while significantly improving flexibility compared to fixed pre-determined warp maps.
Solution Approach 2:
The patent creates a universal distortion compensation system that can handle multiple types of distortions (radial, tangential, keystone) and multiple parameter combinations through a single unified apparatus. The hypersurface parameterization approach allows the same hardware structure to adapt to various distortion scenarios by simply changing the active parameter sets, achieving multi-functionality without requiring separate hardware for each distortion type.
3Measurement precision
If pixel-by-pixel description methods are used for image warping, then transformation accuracy is improved, but hardware implementation cost increases significantly
Solution Approach 1:
The patent extracts the essential transformation information from pixel-by-pixel descriptions by identifying and storing only the critical parameters that define the distortion hypersurfaces. Instead of processing every pixel coordinate individually, the system extracts a compact parameter representation that captures the transformation behavior, significantly reducing hardware complexity while preserving transformation accuracy through the mathematical models.
Solution Approach 2:
The patent replaces the mechanical pixel-by-pixel processing approach with a mathematical field-based approach. By substituting discrete coordinate transformations with continuous hypersurface parameterizations defined by polynomial coefficients, the system achieves the same transformation accuracy with much lower hardware complexity, as the mathematical model naturally interpolates across the image space without requiring explicit pixel-by-pixel computation.
Data Source
AI summary
Dynamic warp map generation system and corresponding method are disclosed. A compactor obtains spatial transformation parameters along with geometric and optical distortion parameters and combines them to form hybrid grid data in a hybrid vector space. This vector space is divided into hybrid blocks. In each hybrid block, the grid dataset is fitted with a hypersurface and the surface coefficients are saved in an interface. A decompactor obtains dynamic control parameters representing varying distortion parameters and generates a hybrid space vector. According to the hybrid space vector, a warp map is decoded from the hypersurface coefficients that compensates for dynamic geometric and optical distortions. In another example of the present invention, the dynamic warp map generation system is used for color gamut transformation.