Camera Image Alignment via One-Dimensional Profile Matching
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Solution Overview
Problem
Conventional dual camera imaging systems face challenges in aligning images from multiple cameras, leading to misplaced objects and high computational costs due to the complexity of processing two-dimensional images for depth perception and dynamic zooming applications.
Innovation Solution
The system transforms two-dimensional images into one-dimensional integral or average profiles and uses a one-dimensional profile matching technique to align the images, reducing computational complexity and processing time by projecting images in the disparity direction and normalizing profiles for accurate matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional two-dimensional image alignment methods are used, then image alignment can be achieved, but hardware complexity and processing time increase significantly
Solution Approach 1:
The patent divides the two-dimensional image alignment problem into multiple one-dimensional profile matching tasks. By projecting images onto one-dimensional profiles along the disparity direction, the complex 2D alignment is segmented into simpler 1D comparisons, reducing hardware complexity while maintaining alignment accuracy.
Solution Approach 2:
The patent transforms the alignment problem from two-dimensional image space to one-dimensional profile space by projecting images along the disparity direction. This dimensionality reduction simplifies the computational complexity and hardware requirements while preserving the essential alignment information needed for accurate image registration.
2Measurement precision
If conventional two-dimensional image alignment methods are used, then image alignment can be achieved, but processing time increases significantly
Solution Approach 1:
The patent segments the 2D image alignment task into multiple 1D profile matching operations. By comparing one-dimensional projections instead of processing full 2D images, the computational workload is divided into smaller, faster operations that reduce overall processing time while maintaining alignment precision.
Solution Approach 2:
The patent reduces processing time by transforming the problem from 2D to 1D through projection along the disparity direction. This dimensional reduction allows for faster computational operations and shorter processing times while preserving the accuracy needed for reliable image alignment.
3Productivity
If conventional pixel-value comparison methods are used, then alignment can be performed, but image objects appear misplaced due to imperfections
Solution Approach 1:
The patent segments the alignment process into profile projection and matching stages, separating the extraction of alignment information from the final registration. This segmentation allows for more robust matching by comparing one-dimensional profiles that capture essential geometric relationships, reducing positioning errors while maintaining processing speed.
Solution Approach 2:
The patent introduces one-dimensional profiles as an intermediary representation between the input images and the final alignment result. These profiles serve as a simplified intermediate form that captures alignment information more reliably than direct pixel comparisons, acting as a mediator that improves both speed and positioning accuracy.
Data Source
AI summary
A multiple camera imaging system, comprising a first camera image sensor configured to obtain a first image of a scene from a first vantage perspective point; a second camera image sensor configured to obtain a second image of the scene from a second vantage perspective point; and an image signal processor (ISP), configured to process the first image and the second image by performing the following steps: producing a first monotone image from the first image, and a second monotone image from the second image; projecting the first monotone image to produce a first one-dimensional profile; and projecting the second monotone image to produce a second one-dimensional profile; extracting a matching information from the first and second one-dimensional profiles by matching the second one-dimensional profile to the first one dimensional profile; using the matching information produce a first processed two-dimensional image, and a second processed two-dimensional image that is aligned with the first processed two-dimensional image.