Further exploration of the object-image metric with image registration in mind

2008 ◽  
Author(s):  
Olga L. Mendoza ◽  
Gregory Arnold ◽  
Peter Stiller
Keyword(s):  
Image Registration ◽  
Object Image ◽  
Image Metric

Study of object image contrast and range of vision in smoke conditions

2020 ◽  
pp. 50-59
Author(s):  
Анатолий Ильич Кицак
Keyword(s):  
Image Registration ◽  
Optical System ◽  
Aerosol Particles ◽  
Image Contrast ◽  
Object Image ◽  
Adverse Conditions ◽  
Black And White ◽  
Polarization Filtering ◽  
Contrast Reduction ◽  
Illumination Source

Представлены результаты исследования зависимостей контраста изображений тестового объекта от оптической плотности различных типов аэрозолей дыма при поляризационной фильтрации излучения подсветки объекта, рассеянного частицами аэрозоля в направлении назад, и в отсутствие фильтрации. Установлено, что формирование изображения объекта с применением метода поляризационной фильтрации излучения помехи обратного рассеяния (ПОР) позволяет снизить скорость уменьшения контраста изображения с увеличением оптической плотности дыма в сравнении с регистрацией изображения без фильтрации ПОР. Полученные результаты могут быть использованы при разработке оптических принадлежностей пожарного-спасателя для наблюдения объектов в неблагоприятных условиях видения: при задымлении, парообразовании, тумане. The relevance of the work is due to the need to develop effective and affordable for mass use technical means of equipping for a firefighter-rescuer, improving the conditions of his work in a smoke-filled environment in a fire. The aim of the work was to study the contrast of the image of a flat black-and-white object with a sharp border of the black-and-white transition formed through various types of smoke aerosols during polarizing filtration of the illumination radiation of the object scattered by aerosol particles in the “back” direction, and in the absence of filtration. The results of the research are presented in the form of dependencies of the object image contrast on the optical density of the smoke aerosol in two image registration schemes, when the receiving optical system is located near the object illumination source at a distance of ~150 mm and when it is located at a distance of ~800 mm from the object illumination source. It is established that the method of forming the image of the object using polarization filtering of radiation backscattering (RBS) reduces the rate of image contrast reduction with an increase in optical smoke density compared with image registration without filtering RBS. The results obtained can be used in the development of optical accessories for firefighter-rescuer to improve the conditions of object observation in adverse conditions of vision: smoke, vaporization, fog.

Developments in automated object-image registration

1995 ◽  
Author(s):  
Ian J. Dowman ◽  
A. Holmes ◽  
V. Vohra
Keyword(s):  
Image Registration ◽  
Object Image

Comparative study of NOTES alone vs. NOTES guided by a new image registration system for navigation in the mediastinum: A study in a porcine model

Endoscopy ◽  
2012 ◽  
Vol 44 (10) ◽  
Author(s):  
H Córdova ◽  
R San José Estépar ◽  
A Rodríguez-D'Jesús ◽  
G Martínez-Pallí ◽  
P Arguis ◽  
...  
Keyword(s):  
Image Registration ◽  
Comparative Study ◽  
Porcine Model ◽  
Registration System

Improved 3D Scene Modeling for Image Registration in Change Detection

2019 ◽  
Vol 2019 (7) ◽  
pp. 465-1-465-7
Author(s):  
Sjors van Riel ◽  
Dennis van de Wouw ◽  
Peter de With
Keyword(s):  
Image Registration ◽  
Change Detection ◽  
Scene Modeling ◽  
3D Scene

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.

INTRODUCING TENSOR ANALYSIS FOR BIOMEDICAL IMAGE REGISTRATION

2018 ◽  
Author(s):  
Wilian Fiirst ◽  
José Montero ◽  
ROGER RESMINI ◽  
Anselmo Antunes Montenegro ◽  
Trueman McHenry ◽  
...  
Keyword(s):  
Image Registration ◽  
Tensor Analysis ◽  
Biomedical Image ◽  
Biomedical Image Registration
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