PSNR-Guided Two-Pass Video Encoding for Cloud Gaming Bandwidth
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Solution Overview
Problem
Existing cloud gaming technologies face issues with unnecessary bandwidth usage and increased end-to-end latency due to inefficient encoding methods, which negatively impact user experience.
Innovation Solution
Adaptive encoding techniques using a peak signal-to-noise ratio (PSNR)-guided two-pass encoding process that employs a content-adaptive statistical model, such as a linear regression model, to determine a minimum quantization parameter (QP) for each frame, reducing the size of encoded frames while maintaining subjective quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional QP selection based on frame size is used to meet target bit rate, then bandwidth usage is controlled, but unnecessary bandwidth consumption occurs and end-to-end latency increases
Solution Approach 1:
The patent changes the parameter basis for QP selection from frame size to PSNR (Peak Signal-to-Noise Ratio). By computing PSNR values and using them to guide QP selection, the system achieves more efficient encoding that reduces both bandwidth consumption and encoding time, thereby lowering end-to-end latency while maintaining quality standards.
Solution Approach 2:
The patent implements a feedback mechanism where PSNR values are computed and used to adjust QP selection dynamically. The system measures the actual encoding quality (PSNR) and uses this feedback to optimize subsequent encoding decisions, ensuring that bandwidth is used efficiently without unnecessary overhead while maintaining acceptable latency levels.
2Quantity of substance
If higher QP values are used to reduce encoded frame size, then bandwidth consumption decreases, but video quality deteriorates
Solution Approach 1:
The patent changes the approach to QP selection by introducing PSNR as an intermediate parameter. Instead of directly selecting QP based on frame size or fixed rules, the system computes PSNR values and uses them to determine optimal QP settings. This ensures that encoded frame size is reduced only when quality thresholds are met, preventing unnecessary quality deterioration.
Solution Approach 2:
The patent makes the QP selection dynamic and adaptive based on actual encoding conditions. By computing PSNR values for different frames and adjusting QP accordingly, the system optimizes the balance between encoded frame size and video quality on a per-frame basis, rather than using static QP values.
3Quantity of substance
If PSNR-guided two-pass encoding is implemented to reduce encoded frame size, then bandwidth consumption is reduced, but encoding complexity increases
Solution Approach 1:
The patent divides the encoding process into two distinct passes: a first pass that computes PSNR values and determines optimal QP settings, and a second pass that performs the actual encoding using the determined parameters. This segmentation allows the system to manage complexity by separating the analysis phase from the execution phase, making the overall process more manageable and efficient.
Solution Approach 2:
The patent performs preliminary actions in the first encoding pass by computing PSNR values and determining optimal QP settings before the actual encoding occurs. This preliminary analysis allows the second pass to proceed more efficiently with pre-determined parameters, reducing the overall encoding complexity compared to making all decisions in real-time during a single pass.
Data Source
AI summary
Techniques for encoding game content for real-time cloud-gaming, and more specifically to using an adaptive statistical model in a moving window of previous frames up to a current frame to adaptively compute a lower-bound of a quantization parameter (QP) that corresponds to a chosen peak signal to noise ratio (PSNR) target. The result of this PSNR-guided encoding is significantly reducing the size of encoded frames (i.e., undershooting a target bit rate when there are no subjective quality losses on those frames using their PSNR as the guidance). These reductions mitigate bandwidth issues and improve the overall user experience because less bits transferred results in faster network transmission and decoding, as well as less platform overhead.