SAR Image Alignment via Tile-Based Complex Correlation
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Solution Overview
Problem
Existing methods for aligning coherent synthetic aperture radar (SAR) images, particularly for coherent change detection, face challenges in achieving precise alignment due to the large size of SAR images and the computational power required, necessitating a more efficient technique to minimize alignment errors.
Innovation Solution
A method involving dividing images into tiles, up-sampling these tiles, and using a complex correlation algorithm to determine offset parameters for precise alignment, which reduces computational power by processing smaller subsets of the image, allowing for accurate alignment with modest computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image alignment methods are applied to large SAR images, then alignment precision can be achieved, but computational power and processing time become excessively large
Solution Approach 1:
The patent divides the large SAR image into multiple smaller tiles (e.g., 100x100 pixels) and processes each tile independently through correlation analysis. This segmentation reduces the computational burden from processing the entire large image to processing only small tile portions, while still achieving accurate alignment through aggregation of tile-level results.
Solution Approach 2:
The patent applies correlation analysis to only a subset of tiles rather than the entire image. By selecting a representative sample of tiles (e.g., 100 tiles out of potentially thousands), the method achieves sufficient alignment precision without the excessive computational cost of processing every pixel and tile in the complete large SAR image.
2Power
If images are divided into smaller tiles for processing, then computational power is reduced, but alignment accuracy may be compromised
Solution Approach 1:
The patent segments the image into tiles and applies correlation analysis to each tile independently. By processing smaller units, the method reduces computational complexity while maintaining accuracy through the aggregation of tile-level alignment results, which collectively represent the overall image alignment.
Solution Approach 2:
The patent creates a correlation map for each tile that represents the alignment relationship between corresponding regions in the two SAR images. These tile-level correlation maps are then aggregated to produce the final alignment transformation, effectively copying and summing up local alignment information to achieve global alignment accuracy.
Data Source
AI summary
A method for the alignment of pairs of complex images of a region, such as may be produced by separate passes of a synthetic aperture radar, is disclosed. The method selects a subset of each image in the form of a plurality of tiles, and calculates a correlation value between corresponding pairs of tiles. Shifts in x and y for each pair where the correlation value exceeds a threshold are then used to calculate values for overall shift, stretch and shear to be applied to one of the images to align it with the other. An iterative least squares approach may be used. As both phase and amplitude information is used in the correlation the technique is suitable for aligning images having little intensity variation. The invention may be used to align images prior to coherent change detection analysis of the images.