Change detection of remote sensing imagein dense urban area based on IR-MAD and mean shift algorithm

doi:10.13474/j.cnki.11-2246.2020.0181

Abstract

Abstract: Change detection of different phase remote sensing image has become one of the indispensable technical means for land use change survey, urban expansion analysis, natural disaster analysis and other environmental issues.This paper proposes a method for detecting remote sensing image changes in dense urban areas based on a combination of IR-MAD and mean shift algorithm. The relative radiation correction of the two-stage image is completed based on the pseudo-invariant feature method, which effectively reduces the registration error between images. Then IR-MAD algorithm is used to perform iterative operation on the corrected image,the mean shift clustering algorithm is used to classify the iterated images, the morphological methods are used to process the segmented images, and finally the change maps are obtained.This paper shows that this method can effectively detect the change area and can be applied to urban change detection and disaster monitoring.

Key words: change detection, relative radiation correction, IR-MAD algorithm, mean shift algorithm, remote sensing

CLC Number:

P237

NIE Qian, ZHAO Yanfu. Change detection of remote sensing imagein dense urban area based on IR-MAD and mean shift algorithm[J]. Bulletin of Surveying and Mapping, 2020, 0(6): 57-62.

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