Decontouring Filter for High Dynamic Range Video Processing
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Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in preserving visual details and reducing contouring artifacts when transitioning from low bit depth to high bit depth dynamic range images, particularly due to one-to-many mappings during prediction operations.
Innovation Solution
Implementing a multi-layer codec with smoothen operations and residual masking to interpolate missing values and select between smoothened and unsmoothened pixel values, using a smoothen operator and residual mask to alleviate false contouring artifacts in high bit depth images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prediction operation from low bit depth BL image data to high bit depth VDR image data is performed, then bit depth expansion is achieved, but contouring artifacts occur due to one-to-many mappings
Solution Approach 1:
A decontouring filter is introduced as an intermediary component between the prediction operation and the final VDR image output. This filter processes the predicted high bit depth image data to remove contouring artifacts while preserving the enhanced bit depth, effectively mediating between the bit depth expansion requirement and the artifact reduction need
Solution Approach 2:
The harmful contouring artifacts are extracted and removed from the predicted high bit depth image through the decontouring filter. The filter identifies and eliminates the artifacts caused by one-to-many mappings while retaining the beneficial high bit depth information
2Stability of the object's composition
If smoothen operations are applied to remove contouring artifacts, then image smoothness is improved, but visual details and image sharpness may be lost
Solution Approach 1:
The decontouring filter applies smoothening operations selectively based on local image characteristics. It analyzes local variance and gradient information to determine which regions require smoothening (contouring-prone areas) and which regions should preserve original details (edge and texture areas), thereby achieving local quality optimization
Solution Approach 2:
The filter applies partial smoothening action only to regions where contouring artifacts are detected, rather than uniformly smoothing the entire image. This selective approach ensures that visual details in non-contouring regions are preserved while still removing artifacts where they occur
Data Source
AI summary
A set of optimized operational parameter values is generated for performing decontouring operations on a predicted image. The predicted image is predicted from a first image mapped from a second image that has a higher dynamic range than the first image. Based on the set of optimized operational parameter values, smoothen operations and selection/masking based on a residual mask are performed on the predicted image. The set of optimized operational parameter values is encoded into a part of a multi-layer video signal that includes the first image, and can be used by a recipient decoder to generate a decontoured image based on the predicted image and reconstruct a version of the second image.