Image Processing Engine Repetitive Pattern Detection Motion Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional motion estimation processes in video image processing often result in inaccurate motion vectors when dealing with images containing repetitive patterns, leading to degradation in perceived image quality due to interpolation errors.
Innovation Solution
An image processing engine that incorporates repetitive pattern detection to adjust the generation of output pictures, using techniques such as periodicity vector analysis and alpha-blending to mitigate interpolation-induced artifacts, ensuring more accurate motion estimation and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion estimation process is used, then processing speed is maintained, but motion vector accuracy deteriorates when repetitive patterns are present
Solution Approach 1:
The patent applies preliminary action by performing repetitive pattern detection before motion estimation. The system detects periodic patterns in the current picture and uses this information to guide the motion estimation process, preventing inaccurate motion vectors from being generated in the first place rather than correcting them afterward.
Solution Approach 2:
The patent applies local quality by adapting the motion estimation approach based on local picture characteristics. Different regions of the picture are processed differently - regions with repetitive patterns use a specialized motion estimation method, while other regions use conventional methods, optimizing accuracy where needed without unnecessarily complicating the entire processing pipeline.
2Manufacturing precision
If motion estimation is performed without repetitive pattern detection, then processing simplicity is maintained, but image quality deteriorates due to interpolation errors
Solution Approach 1:
The system performs repetitive pattern detection as a preliminary step before motion estimation and interpolation. This allows the subsequent processing to be optimized based on the detected patterns, improving image quality without requiring excessive processing time during the critical motion estimation phase.
Solution Approach 2:
The patent applies parameter changes by modifying the motion estimation parameters and interpolation strategy based on the detected repetitive pattern characteristics. When patterns are detected, the system adjusts search ranges, block sizes, and interpolation methods to accommodate the periodic structure, thereby improving image quality while managing processing time.
3Reliability
If conventional interpolation is used with inaccurate motion vectors, then processing speed is maintained, but perceived image quality deteriorates
Solution Approach 1:
The patent applies feedback by using the results of repetitive pattern detection to adjust the motion estimation and interpolation process. The detected pattern information feeds back into the motion vector calculation and interpolation strategy, creating a closed-loop system that adapts to the content being processed and improves reliability without sacrificing excessive productivity.
Data Source
AI summary
An image processing engine, comprising: a frame rate conversion entity configured to: (a) generate output pictures from input pictures, the output pictures comprising a set of first output pictures and a plurality of sets of second output pictures, each set of second output pictures being associated with one of the first output pictures, each of the first output pictures being derived from a respective one of the input pictures; and (b) control generation of the set of second output pictures associated with a particular first output picture based upon repetitive pattern presence detection within a related picture that is either (i) the particular first output picture or (ii) the input picture from which the particular first output picture was derived.