Frame Buffer Compression With Additional Lossless Encoding
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Solution Overview
Problem
Current lossy frame buffer compression schemes are limited in their ability to reduce image data effectively, failing to achieve significant bandwidth and memory savings.
Innovation Solution
A method involving lossy compression followed by additional compression is applied to image data, generating a first and second compressed representation, respectively, to achieve further memory and bandwidth reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If lossless frame buffer compression is used, then image quality is preserved, but bandwidth and memory savings are limited
Solution Approach 1:
The patent applies lossy compression techniques that change the quality parameter of image data by allowing controlled information loss. This enables significantly higher compression ratios (50% or more reduction) compared to lossless methods, directly addressing the bandwidth usage problem while accepting a trade-off in image quality fidelity
Solution Approach 2:
The patent discards redundant or less important image data during compression to achieve higher reduction ratios. By selectively removing certain information that can be reconstructed or is less critical to visual quality, the system achieves greater bandwidth savings than traditional lossless approaches that preserve all original data
2Quantity of substance
If lossy frame buffer compression is applied, then bandwidth and memory savings are achieved, but compression effectiveness is limited
Solution Approach 1:
The patent segments the frame buffer into multiple tiles or blocks that can be independently compressed and processed. This segmentation allows the compression algorithm to work more efficiently on smaller units, achieving better overall compression effectiveness and higher memory savings compared to processing the entire frame buffer as a single unit
Solution Approach 2:
The patent employs dynamic compression strategies that adapt to the content being compressed. By adjusting compression parameters based on local image characteristics, the system achieves improved compression efficiency and greater memory savings compared to static compression approaches with fixed parameters
3Productivity
If additional compression is applied to the first compressed representation, then compression efficiency is enhanced, but processing complexity increases
Solution Approach 1:
The patent applies a first compression pass that prepares the data in an optimized format, making subsequent compression more effective. This preliminary compression action reduces the data volume and structures it in a way that enables the second compression pass to achieve better results with manageable processing complexity
Solution Approach 2:
The first compressed representation serves as an intermediary form between the original image data and the final highly compressed output. This intermediate stage allows the system to achieve enhanced compression efficiency by applying different compression techniques at different stages, balancing processing complexity with compression effectiveness
Data Source
AI summary
Frame buffer compression schemes used for image compression are oftentimes lossless so that the image can be decompressed as close as possible back to its original state. However, lossless compression schemes require that any image data that cannot be successfully compressed (i.e. without losing significant data) be kept in a non-compressed state for transmission and storage. As a result, lossless compression can reduce bandwidth requirements but not memory requirements. The more recently introduced lossy frame buffer compression schemes do allow for some data loss and therefore can save both bandwidth and memory, however, lossy frame buffer compression schemes are limited particularly in the amount by which image data can practically be reduced. The present disclosure provides lossy frame buffer compression which involves an additional compression step, thereby allowing image data to be compressed to a lower rate. This lossy frame buffer compression can reduce both bandwidth and memory usage.