Image Processing Mapping Compression via Function Residuals
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Solution Overview
Problem
Existing image processing methods require large amounts of memory to store precise mappings, such as look-up tables, which are necessary for tasks like color mapping and tonemapping, leading to inefficient use of memory resources.
Innovation Solution
A method for compressing data representative of a mapping in image processing by determining parameters of a function to transform input pixel attribute values into estimated output values, calculating approximate and residual output values, and storing only the function parameters and residual values, thereby reducing memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a look-up table with many hundreds or thousands of entries is used to store precise mappings, then mapping precision is improved, but memory space consumption increases
Solution Approach 1:
The patent segments the mapping data into two parts: a compact function representation (using polynomial coefficients or lookup table indices) and residual correction values. This segmentation allows the main mapping structure to be stored efficiently while preserving precision through residuals, resolving the contradiction between precision and memory usage.
Solution Approach 2:
The patent transforms the mapping representation from storing complete input-output pairs to storing function parameters (coefficients) that define the mapping relationship. This parameter change enables compact storage while maintaining mapping precision through mathematical functions and residual corrections.
2Measurement precision
If a look-up table with many entries is used to store precise mappings, then mapping accuracy is improved, but device complexity increases
Solution Approach 1:
The patent divides the mapping data into function parameters and residual values, creating a simpler hierarchical structure. This segmentation reduces device complexity by organizing data into manageable components while maintaining accuracy through the residual correction mechanism.
Solution Approach 2:
The patent replaces the mechanical approach of storing complete mapping tables with a mathematical function-based system. This substitution reduces device complexity by using computational mathematics (polynomial evaluation, residual addition) instead of direct table lookup for all possible inputs.
Data Source
AI summary
A method for compressing data representative of a mapping for use in image processing. The method comprises determining, based on a plurality of mappings representing a look-up table, parameters of a function for transforming a given set of input pixel attribute values into a set of estimated output pixel attribute values. The method comprises, for a plurality of the sets of input pixel attribute values, determining, based on the function and the set of input pixel attribute values, a set of approximate values of the associated set of output pixel attribute values, and determining, based on the associated set of output pixel attribute values and the set of approximate values, a set of residual output pixel attribute values. The method comprises storing data representative of the parameters of the function and data representative of the sets of residual output pixel attribute values.