An Accurate Image Registration Method Using a Projective Transformation Model

2007 ◽  
Author(s):  
Felix Calderon ◽  
Leonardo Romero
Keyword(s):  
Image Registration ◽  
Projective Transformation ◽  
Transformation Model ◽  
Registration Method

scholarly journals Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images

2021 ◽  
Vol 13 (3) ◽  
pp. 396
Author(s):  
Claudio Ignacio Fernández ◽  
Ata Haddadi ◽  
Brigitte Leblon ◽  
Jinfei Wang ◽  
Keri Wang
Keyword(s):  
Image Registration ◽  
Detection System ◽  
Projective Transformation ◽  
Multispectral Images ◽  
Affine Transformations ◽  
Blue Band ◽  
Greenhouse Production ◽  
Registration Method ◽  
Speeded Up Robust Features ◽  
Close Range

Cucumber powdery mildew, which is caused by Podosphaera xanthii, is a major disease that has a significant economic impact in cucumber greenhouse production. It is necessary to develop a non-invasive fast detection system for that disease. Such a system will use multispectral imagery acquired at a close range with a camera attached to a mobile cart’s mechanic extension. This study evaluated three image registration methods applied to non-georeferenced multispectral images acquired at close range over greenhouse cucumber plants with a MicaSense® RedEdge camera. The detection of matching points was performed using Speeded-Up Robust Features (SURF), and outliers matching points were removed using the M-estimator Sample Consensus (MSAC) algorithm. Three geometric transformations (affine, similarity, and projective) were considered in the registration process. For each transformation, we mapped the matching points of the blue, green, red, and NIR band images into the red-edge band space and computed the root mean square error (RMSE in pixel) to estimate the accuracy of each image registration. Our results achieved an RMSE of less than 1 pixel with the similarity and affine transformations and of less than 2 pixels with the projective transformation, whatever the band image. We determined that the best image registration method corresponded to the affine transformation because the RMSE is less than 1 pixel and the RMSEs have a Gaussian distribution for all of the bands, but the blue band.

An Image Registration Method Based upon Information Theorem on Overlapped Region

2011 ◽  
Vol 58-60 ◽  
pp. 1985-1989
Author(s):  
Yu Chiang Chuang ◽  
Shu Kai S. Fan
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Objective Function ◽  
Projective Transformation ◽  
Intensity Data ◽  
Test Image ◽  
Registration Method ◽  
Practical Applications ◽  
Overlapping Region ◽  
Overlapped Region

Digital image and video have been widely applied to many practical applications due to their simple image acquirement. Image registration is an important image processing for integrating information from images. For Image registration, it is intuitive to orientate images by matching corresponding pixels being considered idealistically identical on the overlapping region. Based on this idea, this article proposes an image registration method that applies the information theorem to the corresponding intensity data. An entropy-based objective function is developed upon the histogram of the intensity differences as to evaluate the similarity between images. Intensity differences represent the differences of the corresponding pixels between the referenced and sensed images on the overlapped region. The sensed image is aligned to the referenced image by minimizing the proposed objective function through iteratively updating the parameters of the projective transformation during the optimization process. The experimental results obtained by means of several test image sets illustrate the effectiveness and feasibility of the proposed image registration method.

Image registration method based on multiresolution for dual-energy subtraction radiography

2012 ◽  
Author(s):  
Takahiro Kawamura ◽  
Norihiro Omae ◽  
Masahiko Yamada ◽  
Wataru Ito ◽  
Kiyosumi Kawamoto ◽  
...  
Keyword(s):  
Image Registration ◽  
Dual Energy ◽  
Registration Method ◽  
Energy Subtraction
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