Image Processor Motion Vector Detection for Grid Patterns
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Solution Overview
Problem
Existing frame rate conversion techniques fail to accurately detect motion vectors in image patterns with periodic or non-periodic brightness changes, such as grid or stripe patterns, leading to erroneous interpolation frames and jittery images.
Innovation Solution
An image processor designates specific areas with periodic or non-periodic brightness changes and uses the relative misalignment of edge components between two frames to determine a motion vector, creating a histogram of shift quantities to identify the highest frequency coincidence points as the motion vector for those areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the matching process is used to detect motion vectors by minimizing pixel difference at symmetric positions, then motion vector detection is simple and fast, but detection accuracy deteriorates for image patterns with periodic brightness changes such as grid or stripe patterns
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently to detect motion vectors. This segmentation allows the system to handle periodic patterns like grids or stripes by analyzing local motion characteristics rather than relying on global matching, thereby improving accuracy without significantly reducing speed
Solution Approach 2:
The patent applies different motion vector detection methods to different regions of the image based on their characteristics. For regions with periodic brightness changes, the system uses specialized processing that considers local edge information and pattern recognition, while other regions use standard matching processes, thus optimizing both speed and accuracy for each local area
2Measurement precision
If edge components are used to detect motion vectors, then detection accuracy improves for general images, but erroneous detection occurs when edge components appear periodically or non-periodically in the same direction
Solution Approach 1:
The patent dynamically adjusts the motion vector detection strategy based on the detected image content. When periodic or non-periodic edge patterns are identified, the system switches to alternative detection methods that analyze temporal changes and spatial relationships differently, preventing erroneous detection while maintaining high reliability for various image types
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor the reliability of detected motion vectors. When inconsistencies are detected (such as impossible motion patterns or patterns that contradict expected object behavior), the system re-evaluates and corrects the motion vector detection, ensuring high reliability even in challenging scenarios with periodic edge patterns
Data Source
AI summary
An image processor includes a motion vector acquisition section for acquiring and outputting an image motion vector in pixel or a predetermined block unit from plural frames included in an input image signal; and a frame interpolation section for generating an interpolated frame by using the motion vector provided by the motion vector acquisition section and for combining the interpolated frame with a frame of the input image signal, thereby composing a signal of a new frame sequence. The motion vector acquisition section includes a first motion vector acquisition section acquiring a motion vector by matching process and a second motion vector acquisition section acquiring a motion vector based on a relative misalignment of a predetermined edge component between two temporally successive frames in a specific area of an input image signal's frame.