scholarly journals THE IMAGE REGISTRATION OF FOURIER-MELLIN BASED ON THE COMBINATION OF PROJECTION AND GRADIENT PREPROCESSING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 723-728
Author(s):  
D. Gao ◽  
X. Zhao ◽  
X. Pan
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Registration Method ◽  
Power Pulse ◽  
Mellin Transformation ◽  
Parallel Image ◽  
Corrected Image ◽  
The Matrix ◽  
Image Pairs ◽  
Partial Blocking

Image registration is one of the most important applications in the field of image processing. The method of Fourier Merlin transform, which has the advantages of high precision and good robustness to change in light and shade, partial blocking, noise influence and so on, is widely used. However, not only this method can’t obtain the unique mutual power pulse function for non-parallel image pairs, even part of image pairs also can’t get the mutual power function pulse. In this paper, an image registration method based on Fourier-Mellin transformation in the view of projection-gradient preprocessing is proposed. According to the projection conformational equation, the method calculates the matrix of image projection transformation to correct the tilt image; then, gradient preprocessing and Fourier-Mellin transformation are performed on the corrected image to obtain the registration parameters. Eventually, the experiment results show that the method makes the image registration of Fourier-Mellin transformation not only applicable to the registration of the parallel image pairs, but also to the registration of non-parallel image pairs. What’s more, the better registration effect can be obtained

Parallel image registration method for snapshot Fourier transform imaging spectroscopy

2017 ◽  
Vol 56 (8) ◽  
pp. 081802
Author(s):  
Yu Zhang ◽  
Shuaishuai Zhu ◽  
Jie Lin ◽  
Feijia Zhu ◽  
Peng Jin
Keyword(s):  
Fourier Transform ◽  
Image Registration ◽  
Imaging Spectroscopy ◽  
Registration Method ◽  
Parallel Image

scholarly journals An Infrared-Visible Image Registration Method Based on the Constrained Point Feature

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1188
Author(s):  
Qingqing Li ◽  
Guangliang Han ◽  
Peixun Liu ◽  
Hang Yang ◽  
Huiyuan Luo ◽  
...  
Keyword(s):  
Image Registration ◽  
Evaluation Method ◽  
Detection Algorithm ◽  
Feature Descriptor ◽  
Registration Accuracy ◽  
Visible Image ◽  
Registration Method ◽  
Visible Images ◽  
Image Pairs ◽  
Point Feature

It is difficult to find correct correspondences for infrared and visible image registration because of different imaging principles. Traditional registration methods based on the point feature require designing the complicated feature descriptor and eliminate mismatched points, which results in unsatisfactory precision and much calculation time. To tackle these problems, this paper presents an artful method based on constrained point features to align infrared and visible images. The proposed method principally contains three steps. First, constrained point features are extracted by employing an object detection algorithm, which avoids constructing the complex feature descriptor and introduces the senior semantic information to improve the registration accuracy. Then, the left value rule (LV-rule) is designed to match constrained points strictly without the deletion of mismatched and redundant points. Finally, the affine transformation matrix is calculated according to matched point pairs. Moreover, this paper presents an evaluation method to automatically estimate registration accuracy. The proposed method is tested on a public dataset. Among all tested infrared-visible image pairs, registration results demonstrate that the proposed framework outperforms five state-of-the-art registration algorithms in terms of accuracy, speed, and robustness.

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.

scholarly journals FIRE: Fundus Image Registration dataset

2017 ◽  
Vol 1 (4) ◽  
pp. 16-28
Author(s):  
Carlos Hernandez-Matas ◽  
Xenophon Zabulis ◽  
Areti Triantafyllou ◽  
Panagiota Anyfanti ◽  
Stella Douma ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Ground Truth ◽  
Fundus Image ◽  
Registration Method ◽  
Evaluation Protocol ◽  
Retinal Fundus Image ◽  
Fair Comparison ◽  
Image Pairs ◽  
Retinal Fundus

Purpose: Retinal image registration is a useful tool for medical professionals. However, performance evaluation of registration methods has not been consistently assessed in the literature. To address that, a dataset comprised of retinal image pairs annotated with ground truth and an evaluation protocol for registration methods is proposed.Methods: The dataset is comprised by 134 retinal fundus image pairs. These pairs are classified into three categories, according to characteristics that are relevant to indicative registration applications. Such characteristics are the degree of overlap between images and the presence/absence of anatomical differences. Ground truth in the form of corresponding image points and a protocol to evaluate registration performance are provided.Results: The proposed protocol is shown to enable quantitative and comparative evaluation of retinal registration methods under a variety of conditions.Conclusion: This work enables the fair comparison of retinal registration methods. It also helps researchers to select the registration method that is most appropriate given a specific target use.

scholarly journals A multicore based parallel image registration method

2009 ◽  
Author(s):  
Lin Yang ◽  
Leiguang Gong ◽  
Hong Zhang ◽  
J.L. Nosher ◽  
D.J. Foran
Keyword(s):  
Image Registration ◽  
Registration Method ◽  
Parallel Image

Digital image processing methods applied to the study of annealing time on semiconductor-metal eutectic composites

1988 ◽  
Vol 46 ◽  
pp. 848-849
Author(s):  
J. Hefter
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Electronic Device ◽  
Processing System ◽  
Average Diameter ◽  
Eutectic Solidification ◽  
Metal Silicide ◽  
The Matrix ◽  
Microscopic Studies

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.

Development of New Image Registration Techniques – A Research Framework

2018 ◽  
Vol 8 (3) ◽  
pp. 50
Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Creative Thinking ◽  
Reference Image ◽  
Transformation Technique ◽  
Research Framework ◽  
Registration Process ◽  
Data Source

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.

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