Frame Decoding with Confidence-Weighted Prediction Residuals
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Solution Overview
Problem
Existing image compression technologies face poor compression performance due to inaccuracies in predicted values for frames with irregular motion or blocked areas, leading to significant coding errors.
Innovation Solution
The proposed method involves configuring a confidence value for predicted values, using a decoder-side apparatus with modules for entropy decoding, motion compensation, and processing to determine reconstructed frames based on predicted values, residuals, and confidence, thereby reducing coding errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If motion estimation and motion compensation technologies are used to predict current frame, then data redundancy is reduced and transmission costs are lowered, but coding error increases for areas with irregular motion or blocked areas
Solution Approach 1:
The patent introduces a confidence map as an intermediary component that mediates between the predicted frame and the residual coding process. The confidence map provides reliability information for each pixel in the predicted frame, allowing the decoder to appropriately handle areas with low prediction confidence (such as irregular motion or blocked areas) versus high confidence areas, thus resolving the contradiction between compression efficiency and prediction accuracy
Solution Approach 2:
The patent changes the parameter space by introducing confidence values as an additional parameter alongside the predicted frame and residual. This allows the system to dynamically adjust the weighting between predicted values and residual values based on the confidence map, enabling adaptive handling of different regions with varying prediction quality
2Productivity
If residual coding is used to encode predicted error, then compression performance is improved for accurate predictions, but coding error becomes significant when predicted value is inaccurate or unavailable
Solution Approach 1:
The patent makes the reconstruction process dynamic by introducing confidence-based weighting. Instead of a static approach where residual coding is always applied uniformly, the system dynamically adjusts the contribution of predicted values versus residual values based on the confidence map, allowing adaptive optimization of compression performance and coding error for different regions
3Measurement precision
If confidence value is configured for predicted values, then reconstructed frame accuracy is improved, but bitstream complexity increases
Solution Approach 1:
The patent segments the confidence information into a separate confidence map that is independently encoded and transmitted in the bitstream. This segmentation allows the confidence data to be processed separately from the image data, enabling improved reconstructed frame accuracy while managing bitstream complexity through structured organization of the encoded data
Data Source
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AI summary
This application discloses encoding and decoding methods and apparatuses, applied to the field of image processing technologies. The method includes: obtaining a bitstream including encoded data of a plurality of image frames; decoding the bitstream to obtain motion information of a current frame; obtaining a predicted value of the current frame based on the motion information; decoding the bitstream to obtain first feature information; obtaining a residual of the current frame and a confidence of the predicted value based on the first feature information; and obtaining a reconstructed frame of the current frame based on the predicted value, the residual of the current frame, and the confidence of the predicted value. This can reduce a coding error caused by low accuracy of predicted content in a coding process, effectively enhancing compression performance.