Image Blending Using Precomputed Rotation Matrices
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Solution Overview
Problem
The challenge lies in efficiently combining images from multiple cameras to produce panoramic or 360-degree images in real-time, as existing methods require numerous cameras and face processing delays due to image distortion from wide-angle lenses, which complicates matching and blending.
Innovation Solution
A system and method that corrects for lens distortion and camera rotation using a rotation matrix, allowing for the efficient combination of images from multiple cameras by calibrating distortion and rotation components, enabling streamlined processing and reduced processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If wide-angle cameras are used to decrease the number of cameras needed for panoramic or 360 degree images, then the number of cameras is reduced, but image distortion complicates matching and blending
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing rotation matrices for various camera angles and positions during a calibration phase. These pre-computed rotation matrices are then reused during real-time image combining operations, eliminating the need for complex real-time distortion calculations and enabling efficient matching and blending of wide-angle images.
2Measurement precision
If many cameras are used to produce panoramic or 360 degree images, then image quality is improved, but processing time increases
Solution Approach 1:
The system performs preliminary calibration to pre-compute rotation matrices for all possible camera combinations and angles. During actual panoramic image generation, these pre-computed matrices are directly applied without real-time calculation, dramatically reducing processing time while maintaining the ability to combine images from multiple cameras for high quality panoramic or 360 degree images.
Solution Approach 2:
The patent segments the image combining process into distinct phases: calibration phase (performed once) and real-time processing phase (repeated operations). This segmentation allows computationally intensive matrix calculations to be performed once and reused, reducing the time penalty for processing multiple camera images.
3Productivity
If real-time processing is required for panoramic or 360 degree images, then processing speed is improved, but the complexity of matching and blending distorted images increases
Solution Approach 1:
The patent resolves the contradiction by pre-computing rotation matrices during calibration that encode the geometric relationships between cameras. During real-time operation, these pre-computed matrices simplify the matching and blending operations to straightforward matrix multiplications, enabling real-time processing without complex runtime calculations.
Data Source
AI summary
A method for combining images includes capturing a first image including a subject from a first camera. A second image is captured from a second camera and the second image includes the subject. First pre-processing functions are applied on the first image to produce a first processed image. The first pre-processing functions include applying a distortion component of a rotation matrix to the first image. The rotation matrix defines a corrected relationship between the first and the second image. Second pre-processing functions are applied on the second image to produces a second processed image. The second pre-processing functions include applying the rotation matrix to the second image. The first processed image and the second processed image are blended in a processing unit to form a composite image.