Image Alignment Hybrid Sequential Reference Error Propagation
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Solution Overview
Problem
Existing image combining stabilization techniques, such as sequential alignment combination, are prone to significant image deterioration if an initial alignment mistake occurs, especially when aligning multiple images, leading to reduced image quality due to the propagation of errors.
Innovation Solution
An image processing apparatus that employs a combination of sequential alignment and reference alignment methods to align and combine images, where sequential alignment is used for adjacent images to minimize framing deviation and reference alignment is used for images further apart to reduce the impact of alignment mistakes, thereby maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sequential alignment combination is used to align multiple images, then image combining stabilization can be achieved, but alignment mistakes propagate and cause significant image deterioration
Solution Approach 1:
The patent divides the alignment process into two independent segments: sequential alignment for adjacent images and reference alignment for images relative to a reference image. This segmentation prevents error propagation by breaking the chain of dependent alignments, where each segment operates independently to reduce cumulative mistakes while maintaining overall alignment accuracy.
2Quantity of substance
If the number of images to be aligned increases, then more images can be combined for stabilization, but alignment mistakes become more remarkable
Solution Approach 1:
The patent introduces a reference image as an intermediary element that mediates the alignment process. Instead of aligning each image sequentially to the previous one, all images are aligned to the reference image, which acts as a stable intermediary point. This approach allows a larger number of images to be aligned without increasing error propagation, as the reference image provides a consistent baseline for all alignments.
3Measurement precision
If reference alignment is used for all images, then alignment mistakes are reduced, but processing time increases for large numbers of images
Solution Approach 1:
The patent merges two alignment methods into a hybrid approach: sequential alignment is used for adjacent images to quickly reduce framing deviation, while reference alignment is used for images relative to the reference image to prevent error propagation. This combination leverages the speed of sequential alignment and the precision of reference alignment, achieving both time efficiency and high alignment precision simultaneously.
Data Source
AI summary
An image processing apparatus that can obtain a high-definition image by reducing an alignment mistake of a plurality of images. The image processing apparatus includes an alignment unit that performs sequential alignment that aligns adjacent images and reference alignment that aligns images other than a reference image to the reference image, and a control unit that controls the alignment unit to align a plurality of images that include a same object and are continuously picked up by an image pickup unit in time series by combining the sequential alignment and the reference alignment.