Fourier transformers for super-resolution images and CT scans

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Fourier transformers for super-resolution images and CT scans

Fourier Image Transformer
arXiv paper abstract https://arxiv.org/abs/2104.02555
arXiv PDF paper https://arxiv.org/pdf/2104.02555.pdf
GitHub https://github.com/juglab/FourierImageTransformer

We present Fourier Image Transformers (FITs), realizations of Fast-Transformers (7), that operate on images via a novel sequential image representation we call Fourier Domain Encoding (FDE). We demonstrate the utility of FITs on two tasks. First, an image super-resolution task (top row), where a given low-resolution image is used to predict a higher resolution version. The second task is tomographic reconstruction (bottom row), where a given set of projection images (a sinogram) is transformed by an encoder-decoder FIT to improve the quality of the reconstructed image w.r.t. filtered backprojection (FBP), a commonly used method for tomographic reconstructions. Note that Fourier Image Transformers solve both tasks in Fourier space, with the final results being obtained by an inverse Fourier transformation (iFFT).

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AI News Clips by Morris Lee: News to help your R&D

Written by AI News Clips by Morris Lee: News to help your R&D

A computer vision consultant in artificial intelligence and related hitech technologies 37+ years. Am innovator with 66+ patents and ready to help a firm's R&D.

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