Image Decoding Interpolation Reuse for Video Processing
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Solution Overview
Problem
Existing image processing methods face inefficiencies in decoding high-resolution video content due to the complexity of encoding schemes like Ericsson Texture Compression (ETC), which require precise parameter matching and interpolation for accurate decoding of encoding units.
Innovation Solution
An image processing method that receives a bitstream containing multiple encoding units, uses interpolation based on reference and weight values to determine sample values, and compares parameters to determine if the encoding units are identical or require separate decoding, allowing for efficient decoding by leveraging interpolation results and difference calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise parameter matching and interpolation are used for accurate decoding of encoding units, then decoding accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent performs parameter comparison and interpolation calculations for the first encoding unit before decoding the second encoding unit. By preparing reference values, weight values, and interpolation results in advance, the system enables the second encoding unit to reuse these pre-computed values, thereby maintaining high decoding accuracy while reducing the overall computational burden through avoided redundant calculations.
Solution Approach 2:
The patent decodes the first encoding unit to generate a reference image block, which is then copied and reused for decoding the second encoding unit. Instead of independently decoding both units with full computational effort, the system creates a copy of the decoding result from the first unit and leverages it for the second unit, significantly reducing computational complexity while preserving decoding accuracy through the copying mechanism.
2Measurement precision
If independent decoding is performed for each encoding unit, then decoding accuracy is maintained, but decoding time increases
Solution Approach 1:
The patent merges the decoding processes of the first and second encoding units by sharing common computational steps. Specifically, it combines the parameter comparison, interpolation, and reference value generation operations into a unified workflow where results from decoding the first unit are integrated into the decoding of the second unit. This merging eliminates redundant operations and reduces total decoding time while maintaining accuracy through the coordinated processing of both units.
Solution Approach 2:
The system performs preliminary decoding of the first encoding unit to generate reference values and interpolation results that are reused for the second encoding unit. By completing preparatory decoding work in advance and storing the results for later reuse, the system reduces the time required for subsequent decoding operations without compromising the accuracy of either unit's decoding.
3Measurement precision
If parameter comparison and interpolation are performed for all encoding units, then decoding accuracy is improved, but processing overhead increases
Solution Approach 1:
The patent applies parameter comparison and interpolation operations selectively rather than uniformly to all encoding units. It performs these computationally intensive operations only when needed—specifically, when decoding the first encoding unit and when the second unit requires reference values that cannot be directly reused. This localized application of processing reduces overall energy consumption and processing overhead while maintaining decoding accuracy in the critical areas where parameter matching is performed.
Solution Approach 2:
The system uses copying of decoding results from the first encoding unit to the second encoding unit, avoiding the need to perform parameter comparison and interpolation for every unit independently. By creating and reusing copies of reference values and interpolation results, the system maintains high decoding accuracy where needed while significantly reducing processing overhead through the elimination of redundant computational operations.
Data Source
AI summary
An image processing method includes receiving a bitstream comprising a first encoding unit and a second encoding unit; acquiring from the bitstream a reference value for decoding of the first coding unit, a weight value for performing interpolation using the reference value to determine one or more sample values, and an index indicating one of the one or more sample values; decoding the first encoding unit using the index and a result of interpolation performed using the reference value and the weight value; and decoding the second encoding unit from the bitstream using the interpolation result used in the decoding of the first encoding unit.