Lagrangian Parameter Calculation for Display Stream Compression
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Solution Overview
Problem
Existing video compression techniques, such as display stream compression (DSC), face challenges in calculating the Lagrangian parameter effectively, leading to suboptimal coding performance due to not considering bit rate and buffer fullness, which affects the selection of appropriate coding modes and image reconstruction quality.
Innovation Solution
The techniques determine the Lagrangian parameter based on the bit rate and buffer fullness by calculating a first parameter from the bit rate ratio and a second parameter from the buffer fullness, combining them to determine a combined Lagrangian parameter for selecting an optimal coding mode that balances rate and distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the Lagrangian parameter is calculated without considering bit rate and buffer fullness, then the calculation is simple, but the coding performance is suboptimal
Solution Approach 1:
The patent changes the parameters used in Lagrangian parameter calculation from static or simplified values to dynamic values that consider bit rate and buffer fullness. Specifically, the patent calculates the Lagrangian parameter λ based on the ratio of actual bit rate to target bit rate and the fullness of the buffer, transforming the calculation from a simple fixed-value approach to a dynamic adaptive approach that responds to real-time encoding conditions.
2Productivity
If the Lagrangian parameter is calculated based on bit rate and buffer fullness, then the coding performance is optimized, but the calculation becomes more complex
Solution Approach 1:
The patent implements feedback mechanisms where the calculated Lagrangian parameter is used to control subsequent encoding decisions, and the actual bit rate and buffer fullness are continuously monitored and fed back into the calculation. This creates a closed-loop system where the encoder adapts its behavior based on the calculated parameter, which itself is derived from real-time system state measurements, thereby optimizing coding performance through adaptive feedback control.
3Quantity of substance
If image compression is applied to pixel data, then the bandwidth requirements are reduced, but the implementation becomes difficult and expensive in conventional display devices
Solution Approach 1:
The patent applies parameter changes by modifying the Lagrangian parameter calculation to be based on dynamic parameters (bit rate ratio and buffer fullness) rather than static parameters. This dynamic adaptation allows the compression algorithm to automatically adjust its behavior to match the capabilities of conventional display devices, achieving effective compression without requiring complex or expensive hardware modifications.
4Device complexity
If the Lagrangian parameter is not accurately determined, then the coding mode selection is simplified, but the image reconstruction quality deteriorates
Solution Approach 1:
The patent introduces dynamics into the Lagrangian parameter calculation by making it adaptive to real-time encoding conditions. Instead of using a fixed or statically determined parameter, the patent dynamically calculates λ based on the current bit rate ratio and buffer fullness, allowing the coding mode selection to respond flexibly to changing conditions while maintaining optimal image reconstruction quality throughout the encoding process.
Data Source
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AI summary
According to certain aspects, an apparatus for coding video data includes a memory for storing the video data and a processor. The memory includes a buffer. The processor is configured to receive the video data to be coded. The processor is further configured to determine a Lagrangian parameter for a coding mode based at least in part on a bit rate of the coding mode and a fullness of the buffer.