Ghosting Artifact Detection in Video Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ghost detection methods in video signals rely on reference signals, which are prone to errors due to transcoding and reformatted during transmission, and are inefficient in terms of computational resources.
Innovation Solution
A method and system for detecting ghosting artefacts in video images without using a reference signal, involving user-input modes for ghosting artefact detection, image field splitting, gradient magnitude calculation, edge image extraction, and confidence score computation to identify and minimize ghosting artefacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reference signal-based ghost detection methods are used, then ghosting detection capability is provided, but detection accuracy deteriorates due to transcoding and reformatting errors
Solution Approach 1:
The patent extracts and removes the reference signal component from the ghost detection system. Instead of using a transmitted reference signal that gets corrupted during transmission, the invention extracts ghosting artifacts directly from the received video signal by comparing adjacent fields, thereby eliminating the source of detection errors while maintaining ghost detection capability
Solution Approach 2:
The patent creates a virtual reference by copying and comparing adjacent video fields instead of using a transmitted reference signal. By overlaying and comparing Field 1 and Field 2, the system generates ghost detection information directly from the video content itself, avoiding transmission-induced errors while preserving detection functionality
2Reliability
If reference signal-based ghost detection methods are used, then ghosting detection is enabled, but computational efficiency deteriorates due to overhead processing
Solution Approach 1:
The patent removes the reference signal overhead from the system by extracting ghosting information directly from the video fields themselves. This eliminates the computational burden of transmitting, receiving, and processing separate reference signals, while maintaining the ability to detect and minimize ghosting artifacts through field comparison operations
Solution Approach 2:
The patent makes the video fields serve multiple functions: they carry both the primary video content and the ghost detection information simultaneously. By using the same video fields for both content delivery and ghost artifact detection, the system eliminates the need for separate reference signals, thereby improving computational efficiency while maintaining detection capability
Data Source
AI summary
A method and system for ghost detection in an image are described. Initially, a mode for detecting ghosting artifact is determined for deciding whether to perform analog or inter field ghosting analysis on the image. Based on the determined mode, a plurality of fields is determined to generate a field overlay image. The image is updated based on the field overlay image and an inter-field average of absolute difference is computed. A significant edge image, a principal edge image, and a delta gradient image are generated. A confidence score indicative of a likelihood of ghosting artifact in the image, is computed based on at least the inter-field average of absolute difference, a first and a second count of pixels in the delta gradient image, a third count of pixels in the principal edge image, and a count of rows of the significant edge image that correspond to the ghosting artifact.