scholarly journals Probably Unknown: Deep Inverse Sensor Modelling Radar

2019 ◽  
Author(s):  
Rob Weston ◽  
Sarah Cen ◽  
Paul Newman ◽  
Ingmar Posner
Keyword(s):  
Sensor Modelling

scholarly journals AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING

2018 ◽  
Vol XLII-2 ◽  
pp. 495-499
Author(s):  
H. G. Kim ◽  
J. H. Son ◽  
T. Kim
Keyword(s):  
Frequency Domain ◽  
Spatial Domain ◽  
Geometric Distortion ◽  
Future Research ◽  
Geometric Correction ◽  
Frequency Matching ◽  
Image Mosaicking ◽  
Important Processing ◽  
Sensor Modelling

In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric distortion, geometric correction of each image should be performed before combining images. However, automated mosaicking images with geometric distortion is not a trivial task. The goal of this paper is the development of automated mosaicking techniques applicable to handle GOCI images. In this paper, we try to extract tie-points by using spatial domain and frequency domain matching and perform the mosaicking of GOCI. The method includes five steps. First, we classify GOCI image slots according to the existence of shorelines by spatial domain matching. Second, we perform precise geometric correction on the slots with shorelines. Third, we perform initial sensor modelling for the slots without shorelines and apply geometric correction based on the initial model. Fourth, the relative relationship between the slots without shorelines and the slots with shorelines is estimated through frequency domain matching. Lastly, mosaicking of geometrically corrected all 16 image slots is performed. The proposed method was verified by applying to real GOCI images. The proposed method was able to perform automated mosaicking even for images without shorelines, and its accuracy and processing time were satisfactory. For future research, we will improve frequency matching to generate multiple tie-points and to analyse the applicability of precise sensor modelling directly from frequency matching. It is expected that the proposed method can be applied to the follow-up sensor of the GOCI, GOCI-II, and other ocean satellite images.

Autoreg 2019

2019 ◽  
Keyword(s):  
Automotive Engineering ◽  
Integration Approach ◽  
Virtual Integration ◽  
Sensor Modelling

Dieser VDI-Bericht ist ausschließlich als PDF-Dokument erschienen! Sie möchten erfahren, was alles an spannenden Themen auf der Tagung in Mannheim präsentiert wurde? Inhalt Jahrmarkt der Innovationen Modellbasierte Folgeregelung für nichtlineare Regelstrecken am Beispiel der Ladedruckregelung – Ein applikationsnaher Entwurf 1 K. Wulff, J. Willkomm, J. Reger, Fachgebiet Regelungstechnik, Technische Universität Ilmenau Nichtlineare modellbasierte prädiktive Regelung der Fahrzeugdynamik in Bezug auf eine aktive Wankstabilisierung und eine Nickreduzierung 3 P. M. Sieberg, S. Blume, S. Reicherts, D. Schramm, Lehrstuhl für Mechatronik, Universität Duisburg-Essen (Doppelpublikation: VDI Verlag Düsseldorf – Springer Nature) Identifikation lokal linearer Modelle am Beispiel der Ladedruckstrecke eines Ottomotors 19 S. Kettlitz, E. Schulz, M. Schultalbers, IAV Automotive Engineering, Gifhorn Generic Sensor Modelling – A Virtual Integration Approach for the Test of ADAS 21 A. Prinz,...

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