Abstract:
Many practical applications requiring multiple related images require image registration. This project proposes a method to handle geometric and intensity transformations in image registration.
Modifying an accurate and fast elastic registration algorithm (Local All-Pass-LAP) to return a parametric displacement field and fitting another parametric expression to estimate intensity changes is the main idea.
Although we demonstrate the methodology using a low-order parametric model, our approach is highly flexible and easily allows much richer parametrisations at low computational cost. We also propose two novel quantitative criteria to assess the accuracy of image alignment (salience correlation) and the number of degrees of freedom (parsimony) of a displacement field.
Our methodology is accurate and computationally efficient as shown by synthetic and real image experiments. We show that the displacement fields are simpler than those from other image registration methods.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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