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A METHOD ON HIGH-PRECISION RECTIFICATION AND REGISTRATION OF
MULTI-SOURCE REMOTE SENSING IMAGERY
Bin Liu \ Guo Zhang b , Xiaoyong Zhu c , Jianya Gong d
a State key laboratory of Information Engineering in Surveying ,Mapping and Remote Sensing, Wuhan University,
Wuhan, China, 430079,benjamin_lb@163.com
b State key laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,
Wuhan, China, 430079, guozhang@whu.edu.cn
c Sehool of Remote Sensing and Information Engineering,Wuhan
University, Wuhan,430079,China,zhuxytop@ 163.com
d State key laboratory of Information Engineering in Surveying ,Mapping and Remote Sensing, Wuhan University, Wuhan, China,
430079, jgong@lmars.whu.edu.cn
KEY WORDS: Image registration; Feature detection; Mutual information; Hill climbing method; Tiny Facet Primitive
ABSTRACT:
For more and more applications on rectification and registration of Multi-source remote sensing imagery, studying in High-precision
rectification and registration becomes significant. In this paper, we propose a method on High-precision rectification and registration
of Multi-source remote sensing imagery, in which we use Mutual Information which is very general and has been used in many
different image registration problems as similarity metrics. In order to enhance the search efficient, improved hill climbing method
has been used. In addition, this method uses a High-precision algorithm: Tiny Facet Primitive. The Chinese-Brazil Earth Resources
Satellite (CBERS) image and Landsat/ETM+ image have been used to test this method. In order to examine the result, we used a
new method which combine the origin image and rectified image to be one image. The result shows very good.
1. INTRODUCTION
Image registration is the process of transforming the different
sets of data which were acquired by sampling the same scene or
object at the same or different times, by the same or different
sensors, from the same or different viewpoint, from different
perspectives into one coordinate system [1]. Registration is very
useful in order to be able to compare or integrate the data
obtained from different measurements. And it has wide
application in remote sensing, medicine, cartography, computer
vision, etc.
With the increasing number of multiple platform remote sensing
missions, many features may have a lot of different remote data
at different spectral ranges, or different resolutions. The
combination of the different data will allow for better analysis
of various phenomena, as well as allow the validation of global
low-resolution analysis by the use of local high-resolution data
analysis [3].
Nowadays, applications on rectification and registration of
Multi-source remote sensing imagery become more and more.
LIU Shi-yin used registration of CBERS images and TM
images to test glacier variations [8]. FAN Hui used combination
of Landsat ETM+ and CBERS to detect the changes of
Huanghe (Yellow) River [9].In this paper, we proposed a
method on High-Precision rectification and registration of
Multi-source Remote Sensing imagery, and use this on CBERS
and Landsat ETM+. Experiment shows a good results on these
two images which has different resolution and got from
different time.
2. IMAGE REGISTRATION METHODOLOGY
In a whole, Image registration methods can be classified into
two categories: feature based methods and intensity based
methods.
The method proposed in this paper, which is intensity based,
consists of the following three steps:
Fig.l. the process of registration
2.1 Feature point detection
In this step, we abstract feature points in the master image to be
control points. Recently, a lot of different interest point
detectors have been proposed with a wide range of definitions
for what points in an image are interesting, in which the most
popular operators are Moravec operator, Forstner operator. Due
to their computational complexity, most of these algorithms are
not well suited to large scale satellite remote sensing data
processing applications [7]. In this paper, we used Moravec
Operator to obtain a lot of feature points. The Moravec
