Interlacing Determination Unit for Frame Deinterlacing
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Solution Overview
Problem
Existing image processing technologies struggle to correctly determine whether frames in various data formats are interlaced, as they rely on metadata flags that may not be present or recognizable, limiting their ability to deinterlace images across different formats.
Innovation Solution
An image processing apparatus with an interlacing determination unit that analyzes the body data of frames to identify interlaced images by comparing top and bottom field images and reducing the influence of motionless subjects, allowing for accurate determination and deinterlacing without relying on specific metadata flags or data formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If metadata flags are used to determine interlaced frames, then determination speed is improved, but compatibility with various data formats deteriorates
Solution Approach 1:
The system performs self-determination of interlaced frames by analyzing image content itself rather than relying on external metadata flags. The interlacing determination unit automatically detects interlaced structures through image processing operations on the frame data, enabling the system to serve itself without depending on format-specific metadata that may not be present in all data formats.
Solution Approach 2:
The patent replaces the metadata-based determination mechanism with an image processing-based mechanism. Instead of reading flags from data structures, the system uses pixel-level analysis through image processing operations to detect interlacing patterns, substituting a mechanical data reading approach with a computational image analysis approach that works across all formats.
2Adaptability or versatility
If image processing on frame body data is performed to determine interlacing, then compatibility with data formats is improved, but processing complexity increases
Solution Approach 1:
The determination process is segmented into distinct operational steps: generating first and second images from the frame data, performing image processing operations on these images, and based on the processing results, determining whether the frame is interlaced. This segmentation breaks down the complex determination task into manageable stages that can be systematically executed.
Solution Approach 2:
The system changes parameters of the image data through processing operations to reveal interlacing characteristics. By transforming the frame body data into processed images with different parameters (such as difference images, gradient images, or other transformed representations), the system can detect interlacing patterns that are not apparent in the original data, enabling format-agnostic determination.
3Measurement precision
If metadata flags are referenced for deinterlacing determination, then determination accuracy is improved for supported formats, but reliability across all formats deteriorates
Solution Approach 1:
The system performs self-determination of interlaced frames by analyzing image content itself rather than relying on external metadata flags. The interlacing determination unit automatically detects interlaced structures through image processing operations on the frame data, enabling the system to serve itself without depending on format-specific metadata that may not be present in all data formats.
Data Source
AI summary
An image processing apparatus that includes an interlacing determination unit and a deinterlacing unit is provided. The interlacing determination unit determines whether or not a frame is an interlaced image by performing image processing on body data of the frame. An interlaced image is an image that includes a top field image and a bottom field image at different times on a timeline. If it was determined that the frame is an interlaced image, the deinterlacing unit deinterlaces the frame and generates a new frame.