Angle-aware object classification in satellite radar imaging
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Solution Overview
Problem
Existing imaging systems face challenges in accurately classifying objects within images due to variations in image data caused by different incidence angles, particularly in satellite-based radar imaging where quantitative and qualitative differences in images collected from varying angles complicate analysis and comparison.
Innovation Solution
A computer-implemented method for classifying objects in images that takes into account the incidence angle from which the image data is collected, using machine learning models to classify objects based on incidence angle data and image data parameters, thereby accounting for the effects of varying angles on image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image data is collected from multiple incidence angles, then the coverage and versatility of the imaging system is improved, but the accuracy of object classification deteriorates due to quantitative and qualitative variations in image data
Solution Approach 1:
The patent applies parameter changes by incorporating incidence angle information as an additional parameter in the machine learning classification process. The system receives incidence angle data and uses it alongside image data parameters to classify objects, thereby compensating for the variations caused by different viewing angles and maintaining classification accuracy across multiple imaging conditions.
2Device complexity
If traditional classification methods are used without considering incidence angle, then the system complexity is kept low, but the classification accuracy deteriorates due to unaccounted variations in image data
Solution Approach 1:
The patent uses machine learning models as an intermediary between the raw image data and the classification output. The ML model is trained to recognize and compensate for incidence angle effects, acting as a mediator that processes both image data and incidence angle information to produce accurate classifications without requiring complex manual intervention or system redesign.
Data Source
AI summary
A computer-implemented method of classifying objects in an image, the method comprising: receiving image data associated with the image; receiving incidence angle data, wherein the incidence angle data is indicative of an incidence angle from which the image data is collected by a detector; and using a machine learning model to classify one or more objects within the image as belonging to one of one or more categories, wherein classifying the one or more objects within the image is based on: the incidence angle data, and respective values of one or more parameters of the image data.