HDR Deblocking Filter Using Pixel Intensity Adaptation
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Solution Overview
Problem
Current video coding schemes, such as JVET and VVC, apply deblocking and filtering uniformly across all content without considering image intensity, leading to suboptimal filtering that can exacerbate display issues in high dynamic range (HDR) content.
Innovation Solution
A system and method for deblocking and filtering HDR content based on pixel intensity, adjusting filtering parameters such as β and tc based on the intensity of coding units and their neighborhoods, to improve filtering effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If deblocking filtering is applied to HDR content, then blocking artifacts are reduced, but processing complexity and computational load increase
Solution Approach 1:
The deblocking filter is segmented into two distinct passes: a high-pass filter applied first to preserve edges and highlights, followed by a low-pass filter to reduce blocking artifacts. This segmentation allows each filter to specialize in specific frequency ranges, reducing the need for complex adaptive processing while maintaining effectiveness.
Solution Approach 2:
The high-pass filter is applied as a preliminary action before the low-pass filter. By first preserving edge information and high-frequency details, the subsequent low-pass filter can operate on pre-processed data that already has protected important features, reducing the computational burden of complex adaptive filtering.
2Object-affected harmful factors
If conventional deblocking filters are used on HDR content, then blocking artifacts are reduced, but gradient calculations become unreliable due to clipped gradients
Solution Approach 1:
The high-pass filter serves as a preliminary action that preserves gradient information before the main deblocking operation. By maintaining high-frequency content and edge information in the high-pass filtered version, the filter can reference this preserved gradient data to make more accurate filtering decisions, avoiding the reliability issues of calculating gradients on already-clipped HDR content.
Solution Approach 2:
The high-pass filtered image acts as an intermediary that mediates between the original HDR content and the final deblocked output. It provides a reference that contains preserved gradient information, which can be used to guide the low-pass filtering operation without being directly corrupted by HDR clipping issues.
3Object-affected harmful factors
If aggressive filtering is applied to reduce blocking artifacts, then artifact reduction improves, but detail preservation deteriorates
Solution Approach 1:
The filtering process is segmented into high-pass and low-pass components applied in sequence. The high-pass filter preserves details and edges by maintaining high-frequency content, while the subsequent low-pass filter gently reduces blocking artifacts without aggressively removing details. This segmentation allows both detail preservation and artifact reduction to coexist.
Solution Approach 2:
The filter uses parameter changes based on local image characteristics, applying different filtering strengths in different regions. By analyzing local variance and gradient information, the filter adapts its strength to preserve details in high-variation regions while more aggressively reducing artifacts in flat regions, achieving both goals simultaneously.
Data Source
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AI summary
A system and method for coding video in which deblocking artifacts are reduced by using modified filtering that is based, at least in part on pixel intensity associated with a coding unit, such that filtering levels are increased as pixel intensity increases. In some embodiments, an offset value or indicator of an offset value for parameters associated with deblocking filter parameters can be associated with a filtering level that is based at least in part on an intensity value.