Abstract
This work introduces a super-resolution (SR) algorithm for range images on the basis of self-guided joint filtering (SGJF), adding the range information of the range image as a coefficient of the filter to reduce the influence of the intensity image texture on the super-resolved image. A range image SR recognition system is constructed to study the effect of four SR algorithms including the SGJF algorithm on the recognition of the laser radar (ladar) range image. The effects of different model library sizes, SR algorithms, SR factors and noise conditions on the recognition are tested via experiments. Results demonstrate that all tested SR algorithms can improve the recognition rate of low-resolution (low-res) range images to varying degrees and the proposed SGJF algorithm has a very good comprehensive recognition performance. Finally, suggestions for the use of SR algorithms in actual scene recognition are proposed on the basis of the experimental results.
| Original language | English |
|---|---|
| Article number | 5185 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Sensors |
| Volume | 20 |
| Issue number | 18 |
| DOIs | |
| Publication status | Published - 2 Sept 2020 |
Keywords
- Combined moment invariant
- Neural network
- Range image SR algorithm
- Target recognition