A Joint Morphological Profiles and Patch Tensor Change Detection for Hyperspectral Imagery

01/20/2022
by   Zengfu Hou, et al.
0

Multi-temporal hyperspectral images can be used to detect changed information, which has gradually attracted researchers' attention. However, traditional change detection algorithms have not deeply explored the relevance of spatial and spectral changed features, which leads to low detection accuracy. To better excavate both spectral and spatial information of changed features, a joint morphology and patch-tensor change detection (JMPT) method is proposed. Initially, a patch-based tensor strategy is adopted to exploit similar property of spatial structure, where the non-overlapping local patch image is reshaped into a new tensor cube, and then three-order Tucker decompositon and image reconstruction strategies are adopted to obtain more robust multi-temporal hyperspectral datasets. Meanwhile, multiple morphological profiles including max-tree and min-tree are applied to extract different attributes of multi-temporal images. Finally, these results are fused to general a final change detection map. Experiments conducted on two real hyperspectral datasets demonstrate that the proposed detector achieves better detection performance.

READ FULL TEXT

page 3

page 6

research
02/24/2022

A spectral-spatial fusion anomaly detection method for hyperspectral imagery

In hyperspectral, high-quality spectral signals convey subtle spectral d...
research
03/24/2023

EMS-Net: Efficient Multi-Temporal Self-Attention For Hyperspectral Change Detection

Hyperspectral change detection plays an essential role of monitoring the...
research
10/02/2020

Morphological segmentation of hyperspectral images

The present paper develops a general methodology for the morphological s...
research
10/27/2020

Hyperspectral Anomaly Change Detection Based on Auto-encoder

With the hyperspectral imaging technology, hyperspectral data provides a...
research
05/05/2019

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

Change detection (CD) is an important application of remote sensing, whi...
research
06/18/2018

Classification of remote sensing images using attribute profiles and feature profiles from different trees: a comparative study

The motivation of this paper is to conduct a comparative study on remote...
research
12/18/2019

Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

Up to the present, an enormous number of advanced techniques have been d...

Please sign up or login with your details

Forgot password? Click here to reset