Video Artifact Detection After Error Concealment
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Solution Overview
Problem
Existing error concealment techniques in video transmission are ineffective in scenarios with significant motion, leading to artifacts such as frozen regions in decoded videos, especially when frames are temporally related.
Innovation Solution
A method for detecting artifacts in decoded images after error concealment involves determining an absolute difference image, identifying candidate regions based on edge pairs and pixel values, and validating these regions using characteristics like edge formation, orientation, and motion profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error concealment techniques are applied to recover lost regions in video transmission, then data loss is reduced, but artifacts such as frozen regions appear in decoded videos with significant motion
Solution Approach 1:
The patent applies preliminary action by performing artifact detection after error concealment but before final video rendering. The system proactively identifies frozen regions and other artifacts in the decoded video frames using difference image analysis and edge detection, allowing for post-processing correction to eliminate these harmful effects before the video is displayed to the user.
2Productivity
If block-based encoding is applied to compress video data, then transmission efficiency is improved, but artifacts are introduced in the rendered video content
Solution Approach 1:
The patent implements feedback by analyzing the decoded video frames for artifacts after error concealment and using this information to identify regions requiring correction. The system calculates difference images between consecutive frames, detects edges and regions with abnormal characteristics, and uses this feedback to locate and potentially correct blocking artifacts and frozen regions, thereby improving overall video quality while maintaining compression efficiency.
3Reliability
If existing error concealment techniques are used in videos with significant motion, then data recovery is attempted, but the techniques become ineffective and produce frozen regions
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the detection thresholds and analysis parameters based on motion characteristics. The system calculates motion compensation and uses motion vectors to adaptively determine regions where artifact detection should be performed, changing the detection parameters according to the actual motion content in the video sequence, thereby maintaining effectiveness in high-motion scenarios.
Data Source
AI summary
A method and system for detection of artifacts in a video after application of an error concealment strategy by a decoder is disclosed. An absolute difference image is determined by subtraction of a current image and a previously decoded image. A threshold marked buffer is determined to replace the pixel values of the absolute difference image with a first pixel value or a second pixel value, based on comparison of pixel values with a first predefined threshold. A candidate region is determined by determining a pair of edges of the threshold marked buffer having length above a second predefined threshold, distance between them above a third predefined threshold, and pixel values between them in the absolute difference image, less than a fourth predefined threshold. Validation of candidate region is based on comparison of characteristics of the candidate region with characteristics of the current image and/or previously decoded images.