Frequency Quantization for Video Encoding Precision
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Solution Overview
Problem
Existing video and image encoding systems face challenges in achieving high precision frequency quantization, particularly when input pixel values exceed output pixel values, leading to data loss and compression artifacts due to premature conversion to lower bit depths and subsampling schemes.
Innovation Solution
The implementation of a high fidelity frequency transform mode that performs frequency transformation on full fidelity pixel values without initial conversion to lower bit depths, generating accurate frequency coefficients for quantization and encoding, thereby maintaining precision and reducing data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If frequency transformation is performed on pixel values converted to lower bit depths, then encoding efficiency is improved, but manufacturing precision deteriorates due to data loss
Solution Approach 1:
The patent performs frequency transformation on full-precision pixel values before quantization, rather than converting to lower bit depths first. This preliminary action on high-precision data ensures that frequency coefficients are calculated with maximum accuracy, avoiding the data loss that would occur from premature bit depth reduction. The full-precision frequency coefficients are then quantized in a controlled manner that preserves encoding accuracy while maintaining efficiency.
2Device complexity
If conversion to lower bit depths is performed early in the encoding process, then device complexity is reduced, but measurement precision deteriorates due to compression artifacts
Solution Approach 1:
The patent changes the order and timing of parameter conversions in the encoding process. Instead of converting pixel bit depth early, the system maintains full precision through the frequency transformation stage and only applies quantization (parameter reduction) after frequency coefficients are generated. This parameter change strategy allows the use of standard frequency transformation algorithms without modification while achieving high precision, as the full-precision input values ensure accurate frequency coefficient calculation even with conventional transform implementations.
3Manufacturing precision
If full fidelity frequency transformation is performed, then encoding accuracy is improved, but loss of substance increases due to higher data requirements
Solution Approach 1:
The patent extracts and processes only the essential full-precision information needed for accurate frequency transformation, rather than maintaining full precision throughout the entire encoding pipeline. By performing frequency transformation on full-precision values and then quantizing the resulting frequency coefficients, the system extracts the most important high-precision data (frequency coefficients) while discarding redundant information. This extraction approach maintains encoding accuracy where it matters most while controlling the overall data volume through subsequent quantization and compression.
Data Source
AI summary
Techniques for high precision frequency quantization for image and video (e.g., frame) encoding are described. According to some embodiments, a computer-implemented method includes receiving a request to encode a video from a first depth of pixel values to a second, lower depth of pixel values at a content delivery service, performing a frequency transformation on a full fidelity of the first depth of pixel values of a frame of the video to generate frequency coefficient values, performing a quantization on the frequency coefficient values to generate quantized frequency coefficient values, encoding the quantized frequency coefficient values of the frame into an encoded frame having the second, lower depth of pixel values by the content delivery service, and transmitting the encoded frame from the content delivery service to a viewer device.


