Non-Linear Color Space Conversion for GPU Gradient Filtering
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Solution Overview
Problem
Existing graphics processing systems face challenges in efficiently converting non-linear color spaces, particularly in converting non-linear YUV samples to linear space, which is computationally intense and not directly supported by hardware, and require complex filtering processes.
Innovation Solution
The proposed solution involves non-linear YUV conversion processes that filter in a non-linear space and convert to a linear space during the conversion process, utilizing up-sampling and color space conversion operations with non-linear values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If linear interpolation methods are used for color space conversion, then computational simplicity is maintained, but filtering artifacts and color banding occur in gradient regions
Solution Approach 1:
The color space conversion is segmented into multiple passes: a first pass performs linear interpolation for most pixels, while a second pass applies non-linear filtering only to specific pixels identified as needing it (those in gradient regions). This segmentation allows the system to maintain computational simplicity for the majority of pixels while improving color accuracy for problematic regions.
Solution Approach 2:
Instead of applying non-linear filtering to all pixels (excessive action), the patent applies it only partially to pixels that benefit most from it. The system identifies pixels in gradient regions and applies non-linear filtering selectively, avoiding the computational overhead of processing every pixel with the more complex algorithm.
2Manufacturing precision
If non-linear filtering is applied to all pixels, then filtering artifacts are reduced, but processing time and computational resources increase significantly
Solution Approach 1:
The pixel population is segmented into two groups: pixels processed with simple linear interpolation and pixels processed with non-linear filtering. The patent uses a hybrid approach where most pixels go through the fast linear path, while only pixels identified as being in gradient regions undergo the slower non-linear filtering process.
Solution Approach 2:
Non-linear filtering is applied partially rather than universally. The system performs non-linear filtering on a subset of pixels that are most likely to exhibit filtering artifacts, thereby reducing the overall processing time while still achieving the benefit of artifact reduction where needed.
3Productivity
If color space conversion is performed without filtering, then processing speed is maintained, but color banding artifacts appear in smooth gradient regions
Solution Approach 1:
The conversion process is segmented into two stages: a first conversion pass that processes all pixels quickly using linear interpolation, and a second conversion pass that applies non-linear filtering only to specific pixels. This segmentation maintains high processing speed for the majority of pixels while improving color smoothness for gradient regions.
Solution Approach 2:
The patent performs a preliminary color space conversion using linear interpolation for all pixels before applying non-linear filtering to specific pixels. This preliminary action establishes baseline color values that can then be refined selectively, maintaining processing efficiency while improving color smoothness where needed.
4Manufacturing precision
If high precision color conversion is applied to all pixels, then color accuracy is improved, but power consumption and computational overhead increase
Solution Approach 1:
The pixel processing is segmented into two categories: pixels processed with standard linear interpolation and pixels processed with high-precision non-linear filtering. This segmentation allows the system to maintain low power consumption for the majority of pixels while applying high precision conversion only where necessary for color accuracy.
Solution Approach 2:
High precision color conversion is applied partially to only those pixels that require it, rather than to all pixels. The patent identifies pixels in gradient regions and applies the computationally intensive non-linear filtering only to these pixels, thereby reducing overall power consumption while maintaining color accuracy where needed.
Data Source
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AI summary
Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. The apparatus may also decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. Further, the apparatus may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels.