Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images

Multi-spatial-resolution change detection is a newly proposed issue and it is of great significance in remote sensing, environmental and land use monitoring, etc. Though multi-spatial-resolution image-pair are two kinds of representations of the same reality, they are often incommensurable superfici...

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Bibliographic Details
Published in:	ISPRS journal of photogrammetry and remote sensing Vol. 116; pp. 24 - 41
Main Authors:	Zhang, Puzhao, Gong, Maoguo, Su, Linzhi, Liu, Jia, Li, Zhizhou
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.06.2016
Subjects:	Change detection Construction contracts data collection Deep neural networks Denoising autoencoder Feature transformation land use Mapping monitoring Neural networks Remedies Remote sensing Representations Segmentation Spatial-resolution Stacked denoising autoencoder Denoising autoencoder Deep neural networks Feature transformation Change detection Stacked denoising autoencoder Spatial-resolution
ISSN:	0924-2716, 1872-8235
Online Access:	Get full text
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