Image registration is a fundamental process in many remote sensing applications, such as image fusion, temporal
change detection. Generally, Algorithms for image registration can be classifeed into two categories: featurebased
and area-based methods. feature-based methods are relatively fast, robust and reliable, and area-based
methods can get high accuracy with high computational cost. Because the result produced by traditional feature
detector may vary with image contrast, it is dificult to set appropriate thresholds automatically for the reference
image and sensed image. To solved these problem, an automatic approach for image registration is presented in
this paper. It use a feature-based approach to get a coarse registration at first. Then, area-based method used
to improve the accuracy of the result. In feature detection stage, it employs a feature detector implemented in
frequency domain to obtain features with normalized measure. Constant thresholds can be applied for different
images. Due to feature matching is time-consuming and computation expensive, line features detected from the
images with approximate direction are mapped into Hough space to estimate the transformation parameters
with Modified Iterative Hough Transform method. Furthermore, it use a hierarchical framework to speed up the
registration process. The experiments show that the approach mentioned above is feasible and efficient.
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