Abstract:
We present an almost lossless affine 2D image transformation method. We extend the theory of the well-known Chirp-z transform to allow fully affine transformation of general n-dimensional images.
We also provide a practical spatial and spectral zero-padding approach to dramatically reduce losses of our transform, which usually introduces blurring artifacts due to sub-optimal interpolation.
Compared to linear interpolation and the best competitor, the proposed method reduces mean squared error by 1800 and 250, respectively.
This paper includes 2D image python code and a basic transform derived from implementation details. Our method produces better images than other methods in demonstration experiments. Runtimes are much longer than toolbox algorithms.
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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