Multiscale Super Resolution without Image Priors
Daniel Fu, Gabby Litterio, Pedro Felzenszwalb, Rashid Zia
TLDR
A multiscale super-resolution technique uses images from different sensor scales to resolve ambiguities, enabling efficient reconstruction without image priors.
Key contributions
- Uses low-resolution images at varying scales to make the super-resolution problem well-posed.
- Demonstrates that pairwise coprime pixel sizes lead to a stable inverse for efficient reconstruction.
- Provides mathematical analysis for least squares error, elucidating the noise-resolution tradeoff.
- Validated through 1D and 2D experiments using CCD hardware binning across a range of pixel sizes.
Why it matters
This paper addresses a fundamental ambiguity in super-resolution by leveraging multiscale sensor data, eliminating the need for image priors. This approach offers a robust and efficient method for high-resolution image reconstruction, with significant implications for common imaging systems and sensor design.
Original Abstract
We address the ambiguities in the super-resolution problem under translation. We demonstrate that combinations of low-resolution images at different scales can be used to make the super-resolution problem well posed. Such differences in scale can be achieved using sensors with different pixel sizes (as demonstrated here) or by varying the effective pixel size through changes in optical magnification (e.g., using a zoom lens). We show that images acquired with pairwise coprime pixel sizes lead to a system with a stable inverse, and furthermore, that super-resolution images can be reconstructed efficiently using Fourier domain techniques or iterative least squares methods. Our mathematical analysis provides an expression for the expected error of the least squares reconstruction for large signals assuming i.i.d. noise that elucidates the noise-resolution tradeoff. These results are validated through both one- and two-dimensional experiments that leverage charge-coupled device (CCD) hardware binning to explore reconstructions over a large range of effective pixel sizes. Finally, two-dimensional reconstructions for a series of targets are used to demonstrate the advantages of multiscale super-resolution, and implications of these results for common imaging systems are discussed.
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