Name
Abstract | ||
|---|---|---|
Quantization is an integral part of image acquisition but also a major performance bottleneck due to the trade-off between dynamic range and resolution. As we discuss in this paper, in contrast, quantization noise can be acquired reliably even beyond the dynamic range by re-purposing recent hardware development. In this paper, we introduce and mathematically analyze an algorithm to recover images from this information, thus giving rise to a novel, single-shot, high-dynamic-range (HDR) imaging approach. Our method directly works with a refined model for sensor outputs at the digitization stage and crucially exploits smoothing anti-aliasing artifacts. We derive recovery guarantees and demonstrate the validity of our approach via computer experiments. Our work suggests re-thinking of the imaging pipeline as seeming sensing artifacts can lead to improved reconstruction when combined with proper computational methodology. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICIP40778.2020.9190872 | 2020 IEEE International Conference on Image Processing (ICIP) |
Keywords | DocType | ISSN |
Quantization (signal) | Conference | 1522-4880 |
ISBN | Citations | PageRank |
978-1-7281-6395-6 | 1 | 0.37 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ayush Bhandari | 1 | 65 | 5.52 |
| Felix Krahmer | 2 | 369 | 27.16 |