De-interlacing Error Correction Using Chrominance-Luminance Segmentation
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Solution Overview
Problem
During the de-interlacing of video data, erroneous image colors occur due to incomplete separation of luminance and chrominance signals, leading to false video color signals and inaccurate processing, which consumes more bandwidth and requires extra buffer memories.
Innovation Solution
A method and apparatus that corrects pixel values of image fields by detecting and separately performing correction operations on chrominance and luminance signals, using three image fields with different polarities to reduce computational complexity and buffer memory requirements, and applying phase inverting techniques to correct chrominance signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If suppression of false video color signals is processed based on a frame or plurality of image fields having different polarities, then false video color signals can be suppressed, but larger bandwidth and extra buffer memories are consumed
Solution Approach 1:
The patent divides the correction process into separate chrominance correction and luminance correction modules, each handling specific aspects of the false color signal suppression. The chrominance correction module processes chrominance signals while the luminance correction module processes luminance signals independently, allowing targeted correction without requiring complete frame-based processing.
Solution Approach 2:
The patent applies different correction strategies to different parts of the signal based on their specific characteristics. Motion detection is applied specifically to determine whether to perform chrominance correction or luminance correction, and edge detection is used to identify regions requiring correction. This localized approach corrects false colors only where needed rather than processing entire frames uniformly.
2Device complexity
If detection operations and correction operations for image chrominance and image luminance are performed separately, then computational complexity is reduced, but processing completeness may be compromised
Solution Approach 1:
The patent segments the correction process into distinct chrominance correction and luminance correction pathways. Motion detection determines which pathway to activate: if motion is detected, chrominance correction is performed; if no motion is detected, luminance correction is performed. This segmentation reduces computational complexity by avoiding simultaneous processing of both correction types while maintaining completeness through conditional execution.
Solution Approach 2:
The patent implements dynamic switching between different correction modes based on motion detection results. The system adapts its processing approach in real-time: when motion is detected in an image field, the system dynamically switches to chrominance correction mode; when no motion is detected, it switches to luminance correction mode. This dynamic adaptation ensures processing completeness while optimizing computational complexity.
3Quantity of substance
If correction is performed using three image fields with different polarities, then buffer memory requirements are reduced, but processing accuracy may be affected
Solution Approach 1:
The patent applies edge detection specifically to identify regions within image fields that require correction, rather than uniformly processing all pixels. By detecting edges and applying correction only to relevant regions, the system maintains high processing accuracy while using fewer image fields and reducing buffer memory requirements.
Solution Approach 2:
The patent performs motion detection and edge detection as preliminary actions before executing the actual correction operations. This preliminary analysis allows the system to identify which regions need correction and prepare appropriate correction strategies in advance, ensuring processing accuracy is maintained while minimizing the number of image fields required and reducing buffer memory usage.
Data Source
AI summary
A method and related apparatus for restraining erroneous image colors are provided for correcting pixel values of three sequential image fields of a video data while de-interlacing the video data. The method is utilized to correct the video data by detecting whether penetrations from luminance signals into chrominance signals or penetrations from chrominance signals into luminance signals occur in the video data. In embodiments of the present invention, the pixel chrominance signals of image fields with the same polarity are utilized to correct the pixel chrominance signals of another image field. Pattern matching and edge detection are utilized to determine whether penetrations from chrominance signals into luminance signals occur.