Volume 36, Number 3, June 2018
|Page(s)||426 - 431|
|Published online||08 October 2018|
Change Detection Algorithm Based on Discrete Wavelet Transforms and Neighborhood Fuzzy C-Means
A new algorithm on Discrete Wavelet Transform (DWT) and neighborhood FCM is proposed to detect change area from remote sensing image. First, the subtraction and ratio image are obtained by the subtraction and ratio method from the two registered remote sensing images; Then, the DWT is applied to the subtraction and ratio image, the region intensity-based and energy-based fusion rules is adopted to the low frequency and high frequency wavelet coefficients, and the inverse DWT is used to obtain the final difference image; At last, the neighborhood FCM is carried out to get the change areas, the spatial distance information and gray difference information are considered in the objective function of FCM, which could avoid misclassification and enhance the detection probability. Experimental results show that the proposed algorithm has strong ability to suppress noise and good detection results; the detection probability of unban change area can reach to 98.45%, whereas, the detection probability is up to 87.5% for the discontinuous forest change area.
Key words: remote sensing image / change detection / DWT / neighborhood FCM
关键字 : 遥感图像 / 变化检测 / 离散小波变换 / 邻域FCM
© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
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