Autosoft Journal

Online Manuscript Access


A Hybrid Registration Approach of Remote Sensing Images for Land Consolidation


Authors



Abstract

Significant developments in the field of remote sensing have widened the application fields of remote sensing. One of the application fields is a land consolidation project. Multi-temporal andor multi-sensor remote sensing provides a unique tool to track land utilization dynamics but requires precise registration of thousands of satellite images. However, automatic registration between remote sensing images is a challenging problem due to the different geometric distortion within the images, the illumination variation and varying resolution. To address this problem, we propose a hybrid automatic image registration scheme (technique), which combines Phase Correlation (PC) method and SIFT descriptor registration together. Based on the specific characteristic of the remote sensing imagery, we apply a Phase Correlation (PC) method first to coarsely pro-register the input image to the reference image. Then, a fine-scale registration process based on the scale invariant feature transform (SIFT) method is constructed. Experiments with Quickbird, CBERS-lremote-sensing images of the land Consolidation area in Beijing demonstrate that the proposed hybrid method is fully automatic and fast. Moreover, the registration accuracy is higher than traditional methods.


Keywords


Pages

Total Pages: 12
Pages: 1121-1132

DOI
10.1080/10798587.2008.10643316


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways


Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Published

Volume: 18
Issue: 8
Year: 2012

Cite this document


References

J. Ros, and C. Laurent, “Description of local singularities for image registration”, Proceedings 18th International Conference on Pattern Recognition, Hong Kong, China, pp. 61–64, 2006.

A Kelman, M. Sollca, and C.V. Stewart, “Keypoint descriptors for matching across multiple image modalities and non-linear intensity variations”, Proceedings IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, USA, pp. 1–7, 2007.

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

TWO YEAR CITATIONS PER DOCUMENT (SJR DATA): 0.993 (2018)
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."





Journal: 1995-Present


CONTACT INFORMATION


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048
EMAIL: tsiepress@gmail.com
WEB: http://www.wacong.org/tsi/