Image Processing for MEMC Border Flicker Reduction
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Solution Overview
Problem
Existing image processors using motion estimation and motion compensation (MEMC) techniques create inconsistent black borders and increase image flickering along the edges of images when the sides of the input image are blurred.
Innovation Solution
An image processing method and processor that computes cumulative counts of bright pixels in binned intervals to identify target intervals near image boundaries, determine side areas, and select adjacent lines as box edges, followed by motion compensation to generate smooth transitions between solid black rims and original pixel data, reducing flickering and enhancing picture quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If black borders are created around regenerated image using MEMC technique, then motion compensation is enhanced, but image flickering increases and picture quality degrades when input image sides are blurred
Solution Approach 1:
The patent applies local quality by differentiating between central area and side area of the image frame. For side areas where flickering occurs, the patent selectively adjusts or suppresses black border creation based on detected bright pixel counts in binned intervals. This localized approach maintains motion compensation benefits in central areas while eliminating harmful flickering effects in side areas where input image quality is degraded.
2Reliability
If black borders are created around regenerated image using MEMC technique, then motion compensation is enhanced, but picture quality consistency with original image decreases
Solution Approach 1:
The patent implements local quality by applying different processing strategies to different regions of the image frame. In side areas with blurred content, the patent uses bright pixel count analysis to determine whether to create black borders or maintain original pixel data, ensuring regional consistency. This preserves overall picture quality consistency while maintaining motion compensation effectiveness.
3Object-generated harmful factors
If bright pixel counting and binned interval analysis is performed to identify side areas, then image flickering is reduced, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the image frame into multiple binned intervals along the vertical direction, with each interval containing M lines. This segmentation enables efficient bright pixel counting within discrete regions, reducing the computational complexity compared to analyzing every pixel individually. The segmented approach maintains accuracy in identifying side areas while lowering processing requirements.
Solution Approach 2:
The patent uses partial action by performing bright pixel counting only in selected binned intervals rather than the entire image frame. By focusing analysis on intervals near image boundaries where flickering is most likely to occur, the patent reduces overall processing complexity while maintaining effectiveness in preventing flickering artifacts.
Data Source
AI summary
An image processing method includes computing N cumulative counts of bright pixels in N binned intervals of an image frame, respectively, and identifying, from a selected range of the N binned intervals, a target binned interval closest to a boundary of the image frame that has a cumulative count of bright pixels exceeding a bin threshold, each binned interval comprising M lines. The method further includes determining whether a line in the target binned interval is in a side area of the image frame according to at least bright pixel counts of a preceding line and a succeeding line in the target binned interval, and selecting from the side area a line adjacent to a central area as a box edge.