Image Stitching Seam Optimization via Spatial Regularization
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Solution Overview
Problem
Conventional image stitching technologies often result in misalignment and reduced quality due to parallax and differing distortion levels between images, especially when shot with moving cameras or different lenses, as the seam passes through objects.
Innovation Solution
An image stitching method and device that calculates costs and forward regularized cumulative costs based on pixel values and relative distances within overlapping areas to determine optimal stitching positions, avoiding seams through objects by using spatial regularization terms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image stitching technology is used, then the stitching process is simple, but the seam passes through objects causing misalignment and reduced image quality
Solution Approach 1:
The patent performs preliminary calculations of forward and backward regularized cumulative costs before determining the final seam path. This preliminary action allows the system to evaluate multiple potential stitching paths and select the optimal one that avoids objects, thereby improving stitching precision while managing complexity through structured pre-computation
Solution Approach 2:
The patent introduces a cost dimension by calculating cumulative costs across the overlapping area, transforming the simple seam selection problem into a multi-dimensional optimization problem. This allows the system to evaluate stitching paths based on multiple criteria (pixel differences, spatial relationships) rather than simple geometric alignment
2Manufacturing precision
If the seam is placed to avoid objects, then image quality improves, but the calculation complexity increases due to forward regularized cumulative costs
Solution Approach 1:
The patent divides the stitching path determination into separate forward and backward calculations, segmenting the complex optimization problem into manageable parts. The forward regularized cumulative cost calculates costs from the starting point, while the backward calculation completes the path optimization, reducing computational burden compared to evaluating all possible paths simultaneously
Solution Approach 2:
The algorithm uses the calculated cumulative costs to automatically determine the optimal seam path without requiring manual intervention or complex external optimization tools. The cost calculation system serves itself by using the computed values to guide the seam selection process, improving precision while maintaining reasonable computational requirements
Data Source
AI summary
An image stitching method and an image stitching device for stitching a first image and a second image are presented. The image stitching method includes: calculating, according to pixel values of the first image and the second image in an overlapping area, a plurality of costs respectively corresponding to a plurality of positions in the overlapping area; calculating, according to the plurality of costs and relative distances between the plurality of positions, a plurality of forward regularized cumulative costs respectively corresponding to the plurality of positions in the overlapping area; determining a seam in the overlapping area according to the plurality of forward regularized cumulative costs, wherein the seam includes a plurality of stitching positions; and stitching the first image and the second image on the basis of the seam to generate a stitched image.