Banding Artifact Detection Using Gradient Mask Analysis
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Solution Overview
Problem
Current video encoding technologies struggle to effectively detect and correct banding artifacts, which are introduced during bit depth conversion and compression, leading to degraded video quality and requiring time-consuming human evaluation.
Innovation Solution
A method for detecting banding artifacts using a mask image based on global gradient changes and local gradients, which creates a gradient field and identifies potential areas containing artifacts, allowing for automatic detection and marking of affected regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If automatic detection methods are used to detect banding artifacts, then time consumption is reduced, but detection accuracy may be compromised due to false positives
Solution Approach 1:
The detection method segments the video image into multiple blocks and analyzes gradient changes within and between blocks. By dividing the image into manageable segments, the system can efficiently process each block to identify banding artifacts while maintaining overall detection accuracy through localized analysis.
Solution Approach 2:
The patent applies different detection criteria to different regions of the image based on their gradient characteristics. Areas with high gradient changes are treated differently from low gradient areas, allowing the system to adapt its detection sensitivity to local image properties and reduce false positives while maintaining comprehensive detection.
2Object-generated harmful factors
If filters are applied to remove smooth regions, then banding artifacts are reduced, but intended banding effects in the video are lost
Solution Approach 1:
The system performs preliminary analysis of gradient fields and identifies potential banding artifact locations before applying any correction. By pre-characterizing the image structure and marking suspected artifact regions, the system can apply targeted corrections only where needed, preserving intentional smooth transitions and banding effects in the original video content.
Solution Approach 2:
The detection method uses feedback from gradient analysis to guide the correction process. By continuously analyzing the gradient fields and comparing them against threshold criteria, the system can distinguish between harmful banding artifacts and intentional visual effects, applying corrections only where the gradient patterns indicate actual artifacts rather than intended design elements.
Data Source
AI summary
A method and system for identifying and determining banding artifacts in digital video content composed of a sequence of moving video pictures includes creating a mask image corresponding to a picture from said sequence of moving video pictures based on global gradient changes to detect potential areas containing banding artifacts. The values of the mask image are scaled thereby making banding artifact detection possible using gradient operators. The banding artifacts are then identified/detected based on the local gradients.