Video Frame Filter Optimization for Decimation and Prediction
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Solution Overview
Problem
Existing video processing technologies face challenges in optimizing decimation filters and prediction filters simultaneously due to their non-linear relationship, which complicates the process of improving video quality during compression and zooming applications.
Innovation Solution
An adaptive decimation filter optimization method is introduced, where the decimation filter is optimized while keeping the prediction filter fixed, and vice versa, using a recursive process to incrementally improve both filters and reduce prediction error, allowing for better video quality by adjusting filter coefficients and pixel taps based on image features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If both decimation filter and prediction filter are optimized simultaneously, then video quality improvement is maximized, but the optimization process becomes computationally intractable due to non-linear relationship
Solution Approach 1:
The patent segments the simultaneous optimization problem into two separate alternating optimization processes: (1) optimizing the decimation filter while keeping the prediction filter fixed, and (2) optimizing the prediction filter while keeping the decimation filter fixed. This segmentation makes the non-linear optimization problem computationally tractable by breaking it into manageable sub-problems that can be solved iteratively.
Solution Approach 2:
The patent implements a dynamic alternating optimization approach where the fixed filter in one iteration becomes the optimized filter in the next iteration. The system dynamically switches between optimizing the decimation filter and optimizing the prediction filter in alternating iterations, allowing both filters to progressively improve video quality without requiring simultaneous optimization.
2Manufacturing precision
If adaptive prediction filter is used to improve target frame quality, then prediction error is reduced, but the decimation filter remains fixed limiting overall improvement
Solution Approach 1:
Instead of only optimizing the prediction filter while keeping the decimation filter fixed (the conventional approach), the patent inverts the approach by optimizing the decimation filter while keeping the prediction filter fixed. This inversion allows the decimation filter to adapt to image features, which indirectly improves prediction quality and enables greater overall system flexibility.
Solution Approach 2:
The patent changes the optimization parameters by switching between optimizing different filter coefficients in alternating iterations. In one iteration, prediction filter coefficients are optimized; in the next iteration, decimation filter coefficients are optimized. This parameter switching enables both filters to adapt independently, improving overall system versatility.
3Ease of operation
If fixed decimation filter is used to simplify processing, then computational complexity is reduced, but video quality improvement is limited
Solution Approach 1:
The patent applies preliminary action by first optimizing the decimation filter using a fixed prediction filter before proceeding to optimize the prediction filter. This preliminary optimization of the decimation filter establishes a good baseline that simplifies subsequent prediction filter optimization and achieves significant video quality improvement early in the process.
Solution Approach 2:
The patent maintains continuity of useful action by implementing alternating iterations where the decimation filter is optimized in one iteration and the prediction filter is optimized in the next iteration. This continuous alternating optimization ensures that both filters are progressively improved without interruption, maintaining processing simplicity while achieving high video quality.
Data Source
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AI summary
An initial decimation filter is applied to an original frame to generate a decimated frame. An optimized prediction filter is extracted from both the decimated frame and the original frame, while the initial decimation filter is held fixed. A predicted from is generated from the optimized prediction filter and the decimated frame, and an optimize decimation filter is extracted from the decimated frame and the predicted frame, while the optimized prediction filter remains fixed.