Piecewise Linear Compression for Display Data Mapping
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Solution Overview
Problem
Existing technologies face challenges in reducing circuit size and complexity for data up-mapping and down-mapping operations, particularly in scenarios where small quantization errors are unacceptable, such as in display imagery processing, due to the need for large and complex circuitry for precise inverse mapping functions.
Innovation Solution
The implementation of piece-wise linear (PWL) compression and decompression operations that do not require a precise inverse of the initial up-mapping function, allowing for custom-tailored breakpoint settings and coefficients to handle only 'used' data points, reducing the need for lookup tables and minimizing circuit size and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If precise inverse mapping functions are used for down-mapping operations, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the down-mapping operation into two independent stages: first applying a compression function, then applying a decompression function. This segmentation allows each function to be simpler and more specialized, avoiding the need for a single complex inverse mapping function. The compression function handles data reduction while the decompression function handles precision restoration, with each optimized for its specific task.
Solution Approach 2:
Instead of directly implementing the traditional inverse mapping approach (up-mapping followed by precise inverse down-mapping), the patent inverts the sequence by using compression first, then decompression. This inverted approach achieves the same goal of maintaining precision while reducing circuit complexity, as the compression-decompression pair can be implemented more efficiently than a precise inverse mapping function.
2Manufacturing precision
If large lookup tables are used for precise inverse mapping, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the lookup table requirement into two smaller tables: one for compression and one for decompression. Each table is optimized for its specific function and contains fewer entries than a full inverse mapping table would require. This segmentation reduces the overall memory footprint while maintaining the precision needed for accurate data representation.
Solution Approach 2:
The patent changes the parameters of the mapping functions by using compression-decompression pairs with specific breakpoint settings and coefficients tailored to actual data distributions. This parameter optimization allows for smaller lookup tables that still achieve high precision, as the functions are tuned to handle only the relevant data ranges and patterns encountered in practice.
3Device complexity
If piece-wise linear compression with custom breakpoints is used, then device complexity is reduced, but manufacturing precision may worsen
Solution Approach 1:
The patent optimizes the parameters of the piece-wise linear functions by setting breakpoints and coefficients based on actual data distribution characteristics. This parameter tuning ensures that the simplified compression-decompression approach maintains high precision by concentrating computational effort where it is most needed, according to the actual data patterns rather than uniform distribution assumptions.
Solution Approach 2:
The patent applies different compression characteristics to different regions of the data range by using piece-wise linear functions with region-specific breakpoints and coefficients. This local optimization ensures high precision in critical regions (such as low spatial frequency areas in display imagery) while using simpler characteristics in less critical regions, thereby maintaining overall precision while reducing complexity.
Data Source
AI summary
Nonlinear compression of high precision image data (e.g., 12-bits per subpixel) conventionally calls for a large sized lookup table (LUT). A smaller sized and tunable circuit that performs compression with piecewise linear compressing segments is disclosed. The piecewise linear data compressing process is organized so that lumping together of plural ‘used’ high precision value points into one corresponding low precision data value point is avoided or at least minimized. In one embodiment, the compressed data is image defining data being processed for display on a nonconventional display screen where the piecewise linearly compressed data can be stored adjacent to other image data in a frame buffer where a composite image is assembled.