Change Detection with Manifold Embedding for Hyperspectral Images

This paper proposes a manifold based approach for change detection in multitemporal hyperspectral images. Manifold representation, using Laplacian Eigenmaps, is applied for dimensionality reduction on stacked temporal datasets and change detection on the reduced datasets. The resulting latent vectors are utilized to cluster the changed vs. unchanged regions. A semi-supervised scheme is also proposed which circumvents the challenging thresholding issue and enables satisfactory binary change detection outputs. The proposed approach is validated on two real bitemporal hyperspectral datasets.

[1]  Yousef Saad,et al.  Trace optimization and eigenproblems in dimension reduction methods , 2011, Numer. Linear Algebra Appl..

[2]  M. Fiedler.  Algebraic connectivity of graphs , 1973 .

[3]  Qian Du,et al.  Band Selection-Based Dimensionality Reduction for Change Detection in Multi-Temporal Hyperspectral Images , 2017, Remote. Sens..

[4]  E. LeDrew,et al.  Application of principal components analysis to change detection , 1987 .

[5]  Melba M. Crawford,et al.  Adaptive Classification for Hyperspectral Image Data Using Manifold Regularization Kernel Machines , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Ruby Kamboj,et al.  Comparative Analysis of Various Change Detection Techniques For Hyperspectral Images , 2016 .

[7]  Lorenzo Bruzzone,et al.  Automatic analysis of the difference image for unsupervised change detection , 2000, IEEE Trans. Geosci. Remote. Sens..

[8]  Melba M. Crawford,et al.  Spectral and Spatial Proximity-Based Manifold Alignment for Multitemporal Hyperspectral Image Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[9]  D. Lu,et al.  Change detection techniques , 2004 .

[10]  Alan R. Gillespie,et al.  A New Approach to Change Vector Analysis Using Distance and Similarity Measures , 2011, Remote. Sens..

[11]  Malgorzata Lucinska,et al.  Spectral Clustering Based on Analysis of Eigenvector Properties , 2014, CISIM.

[12]  Mikhail Belkin,et al.  Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.

[13]  Mahdi Hasanlou,et al.  Hyperspectral change detection: an experimental comparative study , 2018 .

[14]  Jayati Dhawan,et al.  An Exploration Of Various Change Detection Techniques For Hyperspectral Images , 2015 .

[15]  Jean-Yves Tourneret,et al.  A New Multivariate Statistical Model for Change Detection in Images Acquired by Homogeneous and Heterogeneous Sensors , 2015, IEEE Transactions on Image Processing.

[16]  W. Malila.  Change Vector Analysis: An Approach for Detecting Forest Changes with Landsat , 1980 .

[17]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[18]  Francesca Bovolo,et al.  A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges , 2019, IEEE Geoscience and Remote Sensing Magazine.

[19]  Maoguo Gong,et al.  Change-Detection Map Learning Using Matching Pursuit , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Francesca Bovolo,et al.  Rayleigh-Rice Mixture Parameter Estimation via EM Algorithm for Change Detection in Multispectral Images , 2015, IEEE Transactions on Image Processing.