Reweighted Infrared Patch-Tensor Model With Both Nonlocal and Local Priors for Single-Frame Small Target Detection
Nanjing University of Aeronautics and Astronautics · Xi'an Institute of Optics and Precision Mechanics
Abstract
Many state-of-the-art methods have been proposed for infrared small target detection. They work well on the images with homogeneous backgrounds and high-contrast targets. However, when facing highly heterogeneous backgrounds, they would not perform very well, mainly due to: 1) the existence of strong edges and other interfering components, 2) not utilizing the priors fully. Inspired by this, we propose a novel method to exploit both local and nonlocal priors simultaneously. First, we employ a new infrared patch-tensor (IPT) model to represent the image and preserve its spatial correlations. Exploiting the target sparse prior and background nonlocal self-correlation prior, the target-background separation is…
Citation impact
- FWCI
- 149.98
- Percentile
- 100%
- References
- 57
Authors
2Topics & keywords
- Prior probability
- Robust principal component analysis
- Computer science
- Artificial intelligence
- Weighting
- Pattern recognition (psychology)
- Structure tensor
- Tensor (intrinsic definition)
- Sustainable cities and communities