Image Stabilization Using Local Motion Vectors
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Solution Overview
Problem
Existing real-time image capturing systems face challenges in minimizing motion artifacts caused by both camera movement and object movement in the scene, as global motion vectors are ineffective in addressing object motion, which affects only a portion of the scene.
Innovation Solution
The method involves capturing multiple frames, determining local motion vectors between pixels in current and previous frames, and performing temporal filtering to integrate pixels and form the output image, effectively reducing motion artifacts by using a short exposure time and noise reduction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global motion vectors are used to correct image frames, then camera shake artifacts are reduced, but motion artifacts due to object motion in the scene are not reduced
Solution Approach 1:
The patent divides the image frame into multiple blocks and calculates motion vectors for each block independently rather than using a single global motion vector for the entire frame. This segmentation allows different regions of the image to have different motion characteristics, enabling effective correction of both camera shake and object motion artifacts.
Solution Approach 2:
The patent applies local motion compensation by calculating motion vectors for specific blocks rather than globally. Each block's motion vector is used to correct only that local region, allowing the system to handle different motion types (camera shake vs. object motion) in different parts of the image simultaneously.
2Manufacturing precision
If multiple frames are captured and integrated, then noise is reduced, but motion artifacts may increase without proper motion compensation
Solution Approach 1:
The patent performs motion compensation and correction before integrating multiple frames. By calculating motion vectors and correcting each frame's blocks for both camera shake and object motion beforehand, the system ensures that frames are properly aligned and motion artifacts are minimized before the integration process occurs, preventing motion blur in the final composite image.
Solution Approach 2:
The patent uses motion vector calculations as feedback to guide the frame integration process. The motion vectors derived from comparing consecutive frames provide information about camera shake and object motion, which is then used to adjust and correct each frame before integration, creating a feedback loop that improves overall image quality while reducing motion artifacts.
Data Source
AI summary
In one embodiment, a method for reducing motion artifacts in an output image is provided. The method comprises capturing multiple frames of a scene; determining local motion vectors between each pixel in a current frame and a corresponding pixel in the a previous frame; and performing a temporal filtering operation based on the local motion vectors wherein pixels from a plurality frames are integrated to form the output image.