scholarly journals Subpixel Accuracy Analysis of Phase Correlation Shift Measurement Methods Applied to Satellite Imagery

2012 ◽  
Vol 3 (12) ◽  
Author(s):  
S. A. ◽  
A.K. Helmi ◽  
M.A. Fkirin ◽  
S.M. Badwai
Keyword(s):  
Satellite Imagery ◽  
Measurement Methods ◽  
Phase Correlation ◽  
Accuracy Analysis ◽  
Shift Measurement ◽  
Subpixel Accuracy

Research on a Combination of Two Kinds of Phase-modulated Laser Doppler Shift Measurement Methods

2018 ◽  
Vol 47 (4) ◽  
pp. 412003
Author(s):  
杨娜 YANG Na ◽  
杜军 DU Jun ◽  
曲彦臣 QU Yan-chen ◽  
赵卫疆 ZHAO Wei-jiang
Keyword(s):  
Doppler Shift ◽  
Measurement Methods ◽  
Laser Doppler ◽  
Shift Measurement

Phase Correlation Based Image Alignment with Subpixel Accuracy

2013 ◽  
pp. 171-182 ◽  
Author(s):  
Alfonso Alba ◽  
Ruth M. Aguilar-Ponce ◽  
Javier Flavio Vigueras-Gómez ◽  
Edgar Arce-Santana
Keyword(s):  
Phase Correlation ◽  
Image Alignment ◽  
Subpixel Accuracy

scholarly journals Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images

2021 ◽  
Vol 13 (17) ◽  
pp. 3535
Author(s):  
Zhongli Fan ◽  
Li Zhang ◽  
Yuxuan Liu ◽  
Qingdong Wang ◽  
Sisi Zlatanova
Keyword(s):  
Satellite Imagery ◽  
Image Matching ◽  
Satellite Images ◽  
Three Dimensional ◽  
Phase Correlation ◽  
Feature Descriptor ◽  
Matching Method ◽  
Reference Images ◽  
Sar Data ◽  
Optical Satellite Images

Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.

Positional Accuracy Analysis of Satellite Imagery by Circular Statistics

2010 ◽  
Vol 76 (11) ◽  
pp. 1275-1286 ◽  
Author(s):  
A. Cuartero ◽  
A.M. Felicísimo ◽  
M.E. Polo ◽  
A. Caro ◽  
P.G. Rodríguez
Keyword(s):  
Satellite Imagery ◽  
Circular Statistics ◽  
Accuracy Analysis ◽  
Positional Accuracy

scholarly journals Phase correlation functions: FFT vs. FHT

ACTA IMEKO ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 87 ◽  
Author(s):  
Giuseppe Schirripa Spagnolo ◽  
Lorenzo Cozzella ◽  
Fabio Leccese
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Correlation Function ◽  
Pattern Matching ◽  
Phase Correlation ◽  
Critical Element ◽  
Hartley Transform ◽  
Subpixel Accuracy ◽  
2D Fft ◽  
Good Substitute

<p><span lang="EN-GB">The ability to process an image is a crucial skill in many measurement activities. In image processing or pattern recognition, Fast Fourier Transform (FFT) is widely used. In particular, the Phase Only Correlation (POC) method demonstrates high robustness and subpixel accuracy in pattern matching. However, there is a disadvantage in the required memory machine because of the calculation of 2D-FFT. In applications in which the use of memory is a critical element, Fast Hartley Transform (FHT) seems to be a good substitute. In this context, the use of Hartley’s transform can be of interest for apps implemented on portable systems e.g. smartphones. In this article, we present a comparison of the implementations of the phase correlation function using FFT and FHT. Particular attention is given to the analytical steps necessary to implement the POC by means of the Hartley transform.</span></p>

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