Automated change feature extraction systems in remote sensing

Xiaolong Dai

doi:10.1117/12.323212

1 October 1998 Automated change feature extraction systems in remote sensing

Xiaolong Dai

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323212
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

To enhance the ability of remote sensing system to provide accurate, timely, and complete geospatial information at regional and/or global scale, an automated change detection system has been and will continue to be one of the important yet challenging problems in remote sensing. This research was designed to evaluate the requirements and develop the techniques for an automated change detection system at landscape level using various geospatial data including multisensor remotely sensed imagery and ancillary data layers. These techniques are included in three subsystems: automated computer image understanding, multisource data fusion, and database updating and visualization. This paper summarizes what has been achieved so far in this research. The experiments have been focusing on three major interrelated components. In the first component, the impact of misregistration on the accuracy of remotely sensed land cover change detection was quantitatively investigated under Landsat Thematic Mapper images. In the second components, a new feature-based approach to automated multitemporal and multisensor image registration was developed. Feature matching was done in both feature space and image space based on moment invariant distance and chain code correlation. The characteristic of this technique is that it combines moment invariant shape descriptors with chain code correlation to establish the correspondences between regions in two images. In the third component, the algorithms for an automated change detection system utilizing neural networks were developed and implemented. This work has implications on improving the efficiency and accuracy of the change feature extraction and quantification at all levels of applications ranging from local to global in scale.

Citation Download Citation

Xiaolong Dai "Automated change feature extraction systems in remote sensing", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323212

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KEYWORDS

Image registration

Neural networks

Remote sensing

Feature extraction

Earth observing sensors

Algorithm development

Image processing

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