Abstract

Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. Automatic registration of remote-sensing images is a difficult task as it must deal with the intensity changes and variation of scale, rotation and illumination of the images. This paper proposes image registration technique of multi-view, multi- temporal and multi-spectral remote sensing images. Firstly, a preprocessing step is performed by applying median filtering to enhance the images. Secondly, the Steerable Pyramid Transform is adopted to produce multi-resolution levels of reference and sensed images; then, the Scale Invariant Feature Transform (SIFT) is utilized for extracting feature points that can deal with the large variations of scale, rotation and illumination between images .Thirdly, matching the features points by using the Euclidian distance ratio; then removing the false matching pairs using the RANdom SAmple Consensus (RANSAC) algorithm. Finally, the mapping function is obtained by the affine transformation. Quantitative comparisons of our technique with the related techniques show a significant improvement in the presence of large scale, rotation changes, and the intensity changes. The effectiveness of the proposed technique is demonstrated by the experimental results.

Highlights

  • Gad El-karimAbstract— Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources

  • Image registration is a fundamental task in image processing used to match two or more images which are taken at different time, from different sensors or different viewpoints [1]

  • In this paper we present automatic image registration technique of remote sensing image based on the Steerable Pyramid Transform and Scale Invariant Feature Transform (SIFT) descriptors

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Summary

Gad El-karim

Abstract— Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. Automatic registration of remote-sensing images is a difficult task as it must deal with the intensity changes and variation of scale, rotation and illumination of the images. This paper proposes image registration technique of multi-view, multi- temporal and multispectral remote sensing images. The Steerable Pyramid Transform is adopted to produce multi-resolution levels of reference and sensed images; the Scale Invariant Feature Transform (SIFT) is utilized for extracting feature points that can deal with the large variations of scale, rotation and illumination between images .Thirdly, matching the features points by using the Euclidian distance ratio; removing the false matching pairs using the RANdom SAmple Consensus (RANSAC) algorithm. The effectiveness of the proposed technique is demonstrated by the experimental results

INTRODUCTION
PROPOSED IMAGE REGISTRATION TECHNIQUE
Steerable Pyramid Transform
SIFT Feature Point Extraction Algorithm
The proposed Feature Points Matching Using Structural Information
Data Sets
Evaluation
CONCLUSIONS
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