Video Signal Reconstruction Using Asymmetric Residual Transforms
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Solution Overview
Problem
Existing signal processing systems face challenges in efficiently transmitting and reconstructing high-quality video signals, particularly due to the large amounts of data required for scalable encoding techniques, which become cumbersome with the increasing demand for higher quality and definition.
Innovation Solution
The method involves obtaining residual data to reconstruct a signal at a higher quality level using data from a lower quality representation, with transformed residual data being derived from a two-dimensional array of signal elements, where the number of residuals associated with each row can differ, allowing for efficient data transmission and reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scalable encoding techniques are used to reconstruct high-quality signals from lower quality representations, then signal quality is improved, but the amount of data that needs to be stored and transmitted increases
Solution Approach 1:
The residual data is divided into different rows, and transformed residuals are derived by combining residuals from different rows in unequal numbers. This segmentation approach allows the decoder to reconstruct high-quality signals while the encoder transmits fewer transformed residual values, reducing the overall data quantity needed.
Solution Approach 2:
The transformation process uses asymmetric combinations of residuals from different rows, where at least one transformed residual is derived from an unequal number of residuals associated with signal elements from different rows. This asymmetric approach exploits directional correlations in the data to reduce redundancy while maintaining reconstruction quality.
2Manufacturing precision
If more residual data is transmitted to achieve higher quality reconstruction, then reconstruction accuracy is improved, but transmission bandwidth requirements increase
Solution Approach 1:
The invention changes the parameter representation by transforming residual data into a different domain where correlations between different rows can be exploited. By deriving transformed residuals that combine unequal numbers of residuals from different rows, the system achieves efficient compression while maintaining the ability to reconstruct high-quality signals accurately.
3Productivity
If traditional compression techniques are used to reduce data size, then data transmission efficiency is improved, but the ability to recover original signal information is reduced
Solution Approach 1:
Transformed residual data acts as an intermediary representation that preserves essential information from the original signal while requiring fewer bits for transmission. The asymmetric combination of residuals from different rows creates a compressed intermediate form that can be accurately reconstructed at the decoder, maintaining signal information while improving transmission efficiency.
Data Source
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AI summary
A set of reconstruction elements (408) useable to reconstruct a representation of a signal at a relatively high level of quality (402) using data based on a representation of the signal at a relatively low level of quality(404) is obtained. The representation at the relatively high level of quality (402) is arranged as an array comprising at least first and second rows of signal elements. A reconstruction element is associated with a respective signal element in the set. A set of data elements (410) is derived based on the set of reconstruction elements (408). At least one of the data elements (410) is derived from at least two reconstruction elements associated with signal elements from the first row and a different number of reconstruction elements associated with signal elements from the second row.