Adaptive Threshold De-interlacing for Macro Block State Identification
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Solution Overview
Problem
Conventional de-interlacing techniques face misidentification of macro block states, leading to poor video frame display quality due to fixed thresholds, causing issues like stairs or misaligned bevels for weave state misidentification and shredded feathers or rolling edges for bob state misidentification.
Innovation Solution
Adaptive threshold adjustment based on the position of macro blocks within a video frame, dividing the frame into regions with unique basic thresholds to accurately identify macro block states, reducing misidentification and enhancing image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed threshold is used for macro block state identification, then the identification process is simple and fast, but the accuracy of macro block state identification deteriorates leading to misidentification
Solution Approach 1:
The patent divides the video frame into multiple regions (e.g., upper, lower, left, right regions) and assigns different basic thresholds to each region based on its position. This allows each region to be evaluated with a threshold suited to its characteristics, improving identification accuracy without significantly increasing complexity. The devour module then operates on these region-specific thresholds to determine final macro block states.
2Device complexity
If the devour module is used with fixed thresholds, then the processing mechanism is straightforward, but misidentification occurs reducing video frame display quality
Solution Approach 1:
Different basic thresholds are assigned to different regions of the video frame (e.g., upper region, lower region, left region, right region) based on their positions. The devour module uses these region-specific thresholds to evaluate macro blocks, improving reliability and reducing misidentification while maintaining the simplicity of the devour module mechanism.
3Measurement precision
If adaptive threshold adjustment based on region position is implemented, then the accuracy of macro block state identification is improved, but the complexity of the identification process increases
Solution Approach 1:
The patent implements adaptive threshold adjustment by dividing the video frame into regions and assigning different basic thresholds to each region based on position. This improves identification accuracy while controlling complexity through a systematic region-based approach rather than per-macro-block customization.
Solution Approach 2:
The video frame is segmented into multiple regions (upper, lower, left, right), and the identification process is segmented to apply different thresholds to different regions. This segmentation strategy improves accuracy by accounting for regional variations while keeping the overall process manageable through structured division.
Data Source
AI summary
A method for identifying state of macro block of de-interlacing computing and an image processing apparatus are provided, the method is as follows. A video frame is divided into a plurality of regions, where each of the regions includes a plurality of macro blocks. Then, a basic threshold corresponding to each of the regions is provided according to a position of each of the regions in the video frame, and a first macro block is identified to be a first type macro block or a second type macro block according to the basic threshold corresponding to one of the regions where the first macro block of the macro blocks locates. Then, a corresponding de-interlacing computing step is performed on the first macro block according to an result that the first macro block is identified as the first type macro block or the second type macro block.