JOURNAL ARTICLE

Saliency detection based on distance between patches in polarimetric SAR images

Abstract

In this paper, we propose a saliency detection model for polarimetric SAR images based on inter-patch distances. The model is biology-based as it takes the human visual properties into account. Our model consists of local and global saliency detection, which obtained by multi-scale information extraction. What's more, inspired by the distance measures of different image patches, the model takes full use of the coherency matrix which includes the statistical information of pixels and precisely measures the similarity between patches. The experimental results demonstrate the effectiveness of our method.

Keywords:
Artificial intelligence Computer science Pixel Similarity (geometry) Computer vision Pattern recognition (psychology) Polarimetry Synthetic aperture radar Image (mathematics) Scale (ratio) Geography

Metrics

16
Cited By
1.69
FWCI (Field Weighted Citation Impact)
8
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Olfactory and Sensory Function Studies
Life Sciences →  Neuroscience →  Sensory Systems
Photoacoustic and Ultrasonic Imaging
Physical Sciences →  Engineering →  Biomedical Engineering

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