Nested Entropy Encoding for Error-Resilient Motion Vector Coding
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Solution Overview
Problem
Existing video transmission systems face challenges in achieving efficient data compression for high-definition content while maintaining image quality, as conventional motion vector encoding techniques often result in high bit rates that exceed the capabilities of transmission media, leading to potential decoding errors and loss of data redundancy.
Innovation Solution
The implementation of a nested entropy encoding structure that allows for the selection of a candidate set of motion vectors with the highest frequency, enabling efficient coding without trimming duplicate vectors or truncating code symbols, thereby preserving spatial and temporal independence and enhancing error resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional motion vector encoding techniques are used, then motion information can be transmitted, but the bit rate becomes excessively high exceeding transmission media capabilities
Solution Approach 1:
The patent segments the motion vector encoding process into multiple independent candidate sets, where each set contains motion vector predictors from different spatial and temporal locations. This segmentation allows the decoder to parse and decode motion vectors using only the current candidate set without requiring complete predictor sets from all frames, thereby reducing the bit rate while maintaining error resilience.
Solution Approach 2:
The patent implements partial action by allowing the decoder to function with an incomplete set of motion vector predictors. Instead of requiring all candidate sets to be fully decoded for error-free operation, the system enables partial decoding using available candidates, which reduces transmission overhead and bit rate while preserving acceptable error resilience.
2Productivity
If motion vector predictors are trimmed or code symbols are truncated to reduce overhead, then coding efficiency improves, but spatial and temporal independence is lost reducing error resilience
Solution Approach 1:
The patent introduces dynamic candidate set selection, where the encoder and decoder dynamically determine which candidate sets to use based on available data and decoding progress. This dynamic approach allows the system to adaptively maintain spatial and temporal independence among candidate sets, preserving error resilience while improving coding efficiency through selective use of predictors.
Solution Approach 2:
The patent implements a nested structure where multiple candidate sets are organized hierarchically, with each candidate set containing motion vector predictors from different spatial and temporal locations. This nesting allows the decoder to access and decode motion vectors using only the current candidate set, maintaining independence and error resilience while reducing the overhead of transmitting complete predictor sets.
3Measurement precision
If complete predictor sets are required for decoding, then accuracy is maintained, but the system becomes vulnerable to decoding errors when data is lost
Solution Approach 1:
The patent segments the predictor set into multiple independent candidate sets that can be decoded separately. This segmentation allows the decoder to maintain decoding accuracy using only the current candidate set without requiring complete predictor sets from all frames, thereby reducing vulnerability to data loss while preserving measurement precision.
Solution Approach 2:
The patent prepares multiple candidate sets in advance during encoding, with each set containing motion vector predictors from different spatial and temporal locations. This preliminary preparation ensures that the decoder has multiple independent options available, maintaining decoding accuracy even when some data is lost, thereby improving error resilience without sacrificing precision.
Data Source
AI summary
Methods and systems for improving coding decoding efficiency of video by providing a syntax modeler, a buffer, and a decoder. The syntax modeler may associate a first sequence of symbols with syntax elements. The buffer may store tables, each represented by a symbol in the first sequence, and each used to associate a respective symbol in a second sequence of symbols with encoded data. The decoder decodes the data into a bitstream using the second sequence retrieved from a table.