Projects per year
Abstract / Description of output
The number of applications that use depth imaging is rapidly increasing, e.g. self-driving autonomous vehicles and auto-focus assist on smartphone cameras. Light detection and ranging (LiDAR) via single-photon sensitive detector (SPAD) arrays is an emerging technology that enables the acquisition of depth images at high frame rates. However, the spatial resolution of this technology is typically low in comparison to the intensity images recorded by conventional cameras. To increase the native resolution of depth images from a SPAD camera, we develop a deep network built to take advantage of the multiple features that can be extracted from a camera's histogram data. The network then uses the intensity images and multiple features extracted from down-sampled histograms to guide the up-sampling of the depth. Our network provides significant image resolution enhancement and image denoising across a wide range of signal-to-noise ratios and photon levels.
Original language | English |
---|---|
Title of host publication | 2021 29th European Signal Processing Conference (EUSIPCO) |
Subtitle of host publication | Proceedings |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 716-720 |
Number of pages | 5 |
ISBN (Electronic) | 9789082797060 |
DOIs | |
Publication status | Published - 8 Dec 2021 |
Event | 29th European Signal Processing Conference, EUSIPCO 2021 - Dublin, Ireland Duration: 23 Aug 2021 → 27 Aug 2021 |
Publication series
Name | European Signal Processing Conference |
---|---|
Volume | 2021-August |
ISSN (Print) | 2219-5491 |
Conference
Conference | 29th European Signal Processing Conference, EUSIPCO 2021 |
---|---|
Country/Territory | Ireland |
City | Dublin |
Period | 23/08/21 → 27/08/21 |
Keywords / Materials (for Non-textual outputs)
- Deep network
- Guided super-resolution
- LiDAR waveform
- Robust reconstruction
- Unet
Fingerprint
Dive into the research topics of 'Robust and Guided Super-resolution for Single-Photon Depth Imaging via a Deep Network'. Together they form a unique fingerprint.Projects
- 2 Finished