Abstract
The matching accuracy of homonymy points of stereo images is a key point in the development of photogrammetry, which influences the geometrical accuracy of the image products. This paper presents a novel sub-pixel matching method phase correlation using peak calculation to improve the matching accuracy. The peak theoretic centre that means to sub-pixel deviation can be acquired by Peak Calculation (PC) according to inherent geometrical relationship, which is generated by inverse normalized cross-power spectrum, and the mismatching points are rejected by two strategies: window constraint, which is designed by matching window and geometric constraint, and correlation coefficient, which is effective for satellite images used for mismatching points removing. After above, a lot of high-precise homonymy points can be left. Lastly, three experiments are taken to verify the accuracy and efficiency of the presented method. Excellent results show that the presented method is better than traditional phase correlation matching methods based on surface fitting in these aspects of accuracy and efficiency, and the accuracy of the proposed phase correlation matching algorithm can reach 0.1 pixel with a higher calculation efficiency.
Highlights
In the field of digital photography, is one of the important research topics (ARMIN GRUEN, 2012), and its accuracy directly restricts the development of photogrammetry to full digital photogrammetry, influences the geometry accuracy of the subsequent geometric processing
Except being applied in digital photography, as the advantage of phase correlation matching, and it has been applied to other areas such as medical imaging
The method is based on traditional phase correlation matching and improved, and the peak location acquired by calculation according to inherent geometry
Summary
In the field of digital photography, is one of the important research topics (ARMIN GRUEN, 2012), and its accuracy directly restricts the development of photogrammetry to full digital photogrammetry, influences the geometry accuracy of the subsequent geometric processing. Phase correlation matching converts stereo images to frequency domain through Fourier transform, and acquires tie points through the processing of frequency domain information (Kuglin, C.D, 1975). Image matching based on phase correlation method employs the Fourier transform to transform the image to be matched to frequency domain for cross-correlation. It only uses power spectrum phase information of the image blocks in the frequency domain, and reduces the effect of the image content, such as pixel value. If two blocks of image show the same area, peek value of the pulse function can be calculated in the place x, y , and other value, around the peak value, will be far less than the peek value and close to zero
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