Image Stabilization Using Block Motion Vector Thresholding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital image sequence stabilization techniques are inadequate for commercial portable devices due to high computational complexity and implementation costs, and they often fail to efficiently distinguish between unwanted and wanted motions, leading to inefficient stabilization.
Innovation Solution
A method that estimates a global motion vector and compensates for unwanted motion by comparing its amplitude with a threshold, subdividing images into background and foreground regions to optimize stabilization, and using block motion vectors and weighting coefficients to quickly react to small amplitude unwanted movements while avoiding indefinite growth of motion components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional stabilization techniques are used, then motion compensation can be achieved, but computational complexity and implementation costs become excessively high
Solution Approach 1:
The patent segments the image into multiple blocks (e.g., 8x8 pixels) and processes each block independently to compute block motion vectors. This segmentation allows the system to achieve accurate motion compensation while reducing overall computational complexity by dividing the large image processing task into smaller, manageable units that can be processed in parallel or sequentially with lower resource requirements.
Solution Approach 2:
The patent applies stabilization only to portions of the image where motion detection is significant, rather than uniformly processing the entire image. By thresholding motion vectors and applying compensation selectively to blocks exceeding the threshold, the system achieves effective stabilization while reducing unnecessary computational operations on static regions.
2Measurement precision
If global motion estimation is used, then relative motion between images can be estimated, but the system cannot distinguish between unwanted and wanted motions
Solution Approach 1:
The patent computes motion vectors for individual blocks rather than treating the entire image as a single unit. Each block can have its own motion vector and can be independently evaluated against the threshold. This local analysis enables the system to distinguish between unwanted motion (small amplitude blocks) and wanted motion (large amplitude blocks) while maintaining accurate motion estimation for each region.
Solution Approach 2:
The patent introduces a dynamic thresholding mechanism that adapts to different motion scenarios. By comparing block motion vector amplitudes against a configurable threshold, the system dynamically determines whether to apply stabilization to each block, enabling it to adapt to various motion patterns and distinguish between unwanted and wanted motions in real-time.
3Reliability
If motion components are compensated without thresholding, then all motions are corrected, but small amplitude unwanted motions are over-corrected and wanted motions are lost
Solution Approach 1:
The patent implements a feedback mechanism where motion vectors are continuously monitored and compared against a threshold. When a block's motion vector exceeds the threshold, stabilization is applied; when it remains below, no correction is applied. This feedback loop ensures that only significant motions are corrected, preventing over-correction of unwanted motions while preserving wanted motions.
Solution Approach 2:
The patent changes the parameter of motion vector amplitude by introducing a threshold criterion. Instead of uniformly correcting all motion components, the system modifies the correction process based on the amplitude parameter, applying stabilization only when the motion vector magnitude exceeds the threshold, thereby achieving precise control over when correction occurs.
4Device complexity
If simple motion compensation is used, then computational costs are reduced, but the system cannot react quickly to small amplitude unwanted movements
Solution Approach 1:
By segmenting the image into small blocks, the patent enables rapid processing of motion information at a granular level. Each block's motion vector can be computed and evaluated independently, allowing the system to quickly detect and respond to small amplitude unwanted movements without the computational burden of processing the entire image as a single unit.
Solution Approach 2:
The patent applies a thresholding mechanism that enables rapid response to only the most significant motions. By ignoring blocks below the threshold, the system avoids unnecessary processing and can quickly identify and correct unwanted motions when they occur, improving response speed while maintaining computational simplicity through selective processing.
Data Source
AI summary
A method of stabilizing an image sequence, said method comprising the following phases: estimating a first global motion vector comprising a first motion component in a predetermined direction that has associated with it a first respective amplitude and a first respective direction, said first vector being representative of the motion with respect to a reference image of a first image consisting of a pixel matrix, associating said first component with either a wanted motion or an unwanted motion, compensating said first component when it is associated with an unwanted motion, characterized in that the association phase comprises a phase of comparing the first amplitude of said component with a threshold compensation valueTcomphorassigned to the predetermined direction, said first component being associated with an unwanted or wanted motion whenever the first amplitude is, respectively, smaller than said threshold valueTcomphoror greater than/equal to it.