Video Bitstream Parity Hiding for Lower Coefficient Encoding Cost
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Solution Overview
Problem
Current quantization methods in video compression result in high encoding costs due to the need to encode both the sign and absolute value of quantized coefficients, which consumes a large number of bits.
Innovation Solution
Implement parity hiding by partitioning a current block into regions and hiding the parity of quantized coefficients within these regions, using the parity of other coefficients in the region to determine a first quantized coefficient, which is then encoded, reducing the number of bits required for encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current quantization method is used to encode transform coefficients, then encoding completeness is maintained, but encoding cost increases due to high bit consumption
Solution Approach 1:
The patent extracts only the necessary parity information from quantized coefficients and transmits it separately, while the base quantized coefficients are transmitted as before. This extraction approach allows the receiver to reconstruct the original coefficients by combining the transmitted base values with the parity information, thereby reducing the number of bits needed to represent each coefficient while maintaining encoding completeness.
Solution Approach 2:
The patent performs preliminary encoding of quantized coefficients into a compact base representation before transmission. The full coefficient information is prepared in advance by separating it into base values and parity components, allowing the receiver to reconstruct the original values efficiently. This preliminary organization of data reduces the overall bit consumption during transmission.
2Quantity of substance
If parity hiding is implemented on quantized coefficients, then bit consumption is reduced, but decoding complexity increases
Solution Approach 1:
The patent segments the decoding process into distinct stages: first receiving the base quantized coefficients, then receiving the parity information, and finally combining them to reconstruct the original coefficients. This segmentation of the decoding process into modular steps simplifies the overall complexity by breaking down the reconstruction task into manageable operations that can be performed sequentially.
Solution Approach 2:
The patent introduces an intermediary parity component that acts as a bridge between the transmitted base coefficients and the original coefficient values. This parity intermediary carries essential information that enables the receiver to reconstruct the original coefficients without needing to transmit all the original data, thereby reducing bit consumption while managing decoding complexity through a structured intermediate representation.
Data Source
AI summary
A video decoder, a video encoder, and a bitstream are provided. A bitstream is decoded, to obtain P quantized coefficients and a first quantized coefficient in a current region, where the current region is a region in a current block including at least one non-zero quantized coefficient, the first quantized coefficient is obtained by performing parity hiding on a second quantized coefficient in the current region, and P is a positive integer. Then, a parity of the second quantized coefficient is determined according to the P quantized coefficients. The second quantized coefficient having the parity is determined according to the first quantized coefficient and the parity of the second quantized coefficient.