Bitemporal multispectral images unsupervised change detection based on undecimated wavelet transform and chi-squared transform

Aiye Shi; Shaohong Shen; Chao Wang; Zhenli Ma

doi:10.1117/1.JRS.12.016025

20 February 2018 Bitemporal multispectral images unsupervised change detection based on undecimated wavelet transform and chi-squared transform

Aiye Shi, Shaohong Shen, Chao Wang, Zhenli Ma

Author Affiliations +

Funded by: CRSRI Open Research Program, Changjiang Science Institute of China, National Natural Science Foundation of China (NSFC), Natural Science Foundation of China, National Natural Science Foundation of Jiangsu Province, China the Natural Science Foundation of JiangSu Province (Youth Fund)

Journal of Applied Remote Sensing, Vol. 12, Issue 1, 016025 (February 2018). https://doi.org/10.1117/1.JRS.12.016025

Abstract

Ordinary unsupervised change detection methods are mostly applied to the magnitude of spectral change vector (MSCV) of bitemporal images. However, the information contained in the different bands of the difference image is not fully exploited. We propose an unsupervised change detection method based on undecimated wavelet transform (UWT) in combination with chi-squared transform (CT). First, the UWT is applied to the difference image, and multiresolution images of each band of the difference image are obtained. Second, spatial constraint CT (SCT) is applied to the same resolution levels of each band of the difference image. Then, the results of SCT at all resolution levels are fused by a majority voting rule. After that, the fusion result as an initial solution of change detection is further improved by a Markov random field (MRF) model. In the implementation of the MRF model, the nonnegative matrix factorization is applied to fuse the MSCV and spectral angle mapper of bitemporal images to obtain the difference image. The experiments on three sets of multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.

Citation Download Citation

Aiye Shi, Shaohong Shen, Chao Wang, and Zhenli Ma "Bitemporal multispectral images unsupervised change detection based on undecimated wavelet transform and chi-squared transform," Journal of Applied Remote Sensing 12(1), 016025 (20 February 2018). https://doi.org/10.1117/1.JRS.12.016025

Received: 4 July 2017; Accepted: 25 January 2018; Published: 20 February 2018

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KEYWORDS

Image fusion

Multispectral imaging

Magnetorheological finishing

Wavelet transforms

Detection and tracking algorithms

Expectation maximization algorithms

Image resolution

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