Video Encoding Bit Estimation via AC Coefficient Analysis
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Solution Overview
Problem
Existing video encoding technologies face inefficiencies in rate control algorithms due to computationally expensive entropy coding processes, requiring multiple iterations to achieve optimal quantization levels and modes, and lack effective methods for estimating the number of bits required to encode macroblocks without exact computation.
Innovation Solution
A system and method that includes a bit estimator using a linear function of non-zero AC coefficients from the current and neighboring macroblocks to estimate the number of bits required for encoding, allowing for the selection of optimal encoding modes without performing full entropy coding each time, and incorporating a feedback loop for quantization parameter adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If entropy coding is performed for each macroblock to calculate exact bit requirements, then measurement precision of bit count is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent replaces expensive entropy coding operations with cheap proxy measurements (SAD, zero-crossing counts, run-length statistics) that can be computed rapidly. These proxy metrics serve as disposable indicators of bit requirements without needing to perform actual encoding, thus resolving the contradiction between measurement precision and computational complexity.
Solution Approach 2:
The patent introduces intermediary statistical features (zero-crossing counts, run-length distributions, SAD values) that mediate between the raw macroblock data and the final bit count estimation. These intermediaries capture essential compression characteristics without requiring full entropy coding, enabling accurate estimation with reduced computational burden.
2Manufacturing precision
If multiple iterations of entropy coding are performed to achieve optimal quantization levels, then video quality is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary statistical analysis (calculating zero-crossing counts, run-length statistics, SAD values) before actual encoding to predict bit requirements and guide quantization parameter selection. This preliminary action enables near-optimal quality achievement without requiring multiple time-consuming entropy coding iterations.
Solution Approach 2:
The patent changes the approach from iterative entropy coding to direct statistical parameter measurement. By measuring properties like zero-crossing counts and run-length distributions directly from transform coefficients, the system determines optimal quantization levels without repeated encoding iterations, thus improving processing time while maintaining video quality.
3Measurement precision
If variable length coding is performed for each macroblock to determine bit requirements, then bit rate control accuracy is improved, but computational expense increases
Solution Approach 1:
The patent creates simplified copies or proxies of the actual encoding process by measuring statistical properties (zero-crossings, run-lengths) that correlate with bit requirements. These proxy measurements replicate the essential information needed for bit rate control without performing the full variable length coding operation, thus reducing computational expense while maintaining accuracy.
Data Source
AI summary
An embodiment of the present disclosure relates to system comprises an encoding device. Said encoding device comprises a compression unit, a quantizer, a bit estimator, a bit rate encoder and a variable length encoder. An embodiment also is a method of encoding. Said method estimates a number of bits to encode a macroblock after compressing the data stream. Then the estimated bit encoded by a bit rate encoder and further quantized by the quantizer to get the final encoded bit stream. The number of bits required to encode a macroblock is estimated after the quantization process and before the encoding process. The macroblock bit estimator estimates the number of bits required to encode a particular macroblock depending on the quantized AC coefficients of that macroblock and the quantized AC coefficients of the neighboring frames normalized at a macroblock level.