Adaptive Loop Filter Coefficient Constraints for Video Hardware
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Solution Overview
Problem
The high complexity and cost of hardware implementation of Adaptive Loop Filter (ALF) in video coding systems due to large dynamic ranges of ALF coefficients, which also makes them sensitive to noise.
Innovation Solution
Constraining the data range of ALF coefficients to reduce the number of multipliers required, with center coefficients limited to [0.0, 2.0) and non-center coefficients to [-1.0, 1.0), allowing for more efficient hardware implementation by reducing the bit width of multipliers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the data range of ALF coefficients is not constrained, then the filter can achieve higher picture quality through adaptive filtering, but the hardware implementation complexity and cost increase due to large dynamic ranges requiring more multipliers
Solution Approach 1:
The patent applies parameter changes by constraining the dynamic range of ALF coefficients to specific intervals (center coefficients in [0.0, 2.0) and non-center coefficients in [-1.0, 1.0)). This parameter constraint reduces the bit width requirements for multiplier operations, directly decreasing hardware complexity while preserving sufficient filtering effectiveness for picture quality enhancement
2Adaptability or versatility
If the data range of ALF coefficients is not constrained, then the filter has greater flexibility in adaptation, but the system becomes more sensitive to noise and requires more hardware resources
Solution Approach 1:
By changing the parameter constraints of ALF coefficients to bounded ranges, the patent reduces noise sensitivity while maintaining adaptability. The constrained ranges prevent extreme coefficient values that amplify noise, and the selective application to different coefficient positions (center vs. non-center) preserves the necessary flexibility for adaptive filtering across different picture regions
3Device complexity
If the bit width of multipliers is reduced through coefficient constraint, then the hardware cost decreases, but the precision of filtering operations may be compromised
Solution Approach 1:
The patent carefully selects constraint ranges that balance precision and cost: center coefficients are constrained to [0.0, 2.0) and non-center coefficients to [-1.0, 1.0). These ranges are wide enough to maintain sufficient filtering precision for quality enhancement while narrow enough to reduce multiplier bit width requirements, achieving an optimal trade-off between hardware cost and operation precision
Data Source
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AI summary
Methods and apparatuses for processing of coded video using ALF are disclosed. Embodiments according to the present invention apply ALF with constrained data range to reconstructed video data. The ALF parameters comprise a center coefficient, one or more non- center coefficients, and an offset term. As an example, the constrained data range for the center coefficient is selected from [0.0, 2.0) and [0.5, 1.5). In another example, the constrained data range for said one or more non-center coefficient is selected from [-1.0, 1.0) and [-0.5, 0.5). The constrained data range can also be applied to the offset term. For example the range of [-2D/N, (2D-1)/N) can be applied to the offset term, wherein D denotes pixel bit depth and N is a power-of-two integer. Alternatively, the constrained data range for the offset term can be [-2M,2M), wherein M is an integer.