Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack

Autor: Renato J. Cintra, Mats I. Pettersson, Bruna Gregory Palm, Hans Hellsten, Viet T. Vu, Fábio M. Bayer, Dimas I. Alves, Renato Machado, Patrik Dammert
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Signal Processing (eess.SP)
FOS: Computer and information sciences
geometry
Computer science
0211 other engineering and technologies
02 engineering and technology
lcsh:Chemical technology
Biochemistry
Analytical Chemistry
Constant false alarm rate
forest
image stack
0202 electrical engineering
electronic engineering
information engineering
lcsh:TP1-1185
army
Computer vision
Annan elektroteknik och elektronik
multi-pass
Instrumentation
Image and Video Processing (eess.IV)
article
Truncated mean
detection algorithm
Atomic and Molecular Physics
and Optics
Wavelength
Autoregressive model
Synthetic aperture radar
Backscatter
ground scene prediction
probability
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
FOS: Physical sciences
Statistics - Applications
Article
Image (mathematics)
Methodology (stat.ME)
telecommunication
FOS: Electrical engineering
electronic engineering
information engineering
Applications (stat.AP)
Electrical Engineering and Systems Science - Signal Processing
Electrical and Electronic Engineering
Representation (mathematics)
Statistics - Methodology
021101 geological & geomatics engineering
CARABAS II
Other Electrical Engineering
Electronic Engineering
Information Engineering
business.industry
020206 networking & telecommunications
prediction
Electrical Engineering and Systems Science - Image and Video Processing
SAR images
Physics - Data Analysis
Statistics and Probability
Artificial intelligence
business
Data Analysis
Statistics and Probability (physics.data-an)
Zdroj: Sensors
Volume 20
Issue 7
Sensors, Vol 20, Iss 2008, p 2008 (2020)
Sensors (Basel, Switzerland)
ISSN: 1424-8220
DOI: 10.3390/s20072008
Popis: This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed of images from the same scene acquired at different instants with the same flight geometry. The considered methods for obtaining the ground scene prediction include (i) autoregressive models
(ii) trimmed mean
(iii) median
(iv) intensity mean
and (v) mean. It is expected that the predicted image presents the true ground scene without change and preserves the ground backscattering pattern. The study indicates that the the median method provided the most accurate representation of the true ground. To show the applicability of the GSP, a change detection algorithm was considered using the median ground scene as a reference image. As a result, the median method displayed the probability of detection of 97 % and a false alarm rate of 0 . 11 / km 2 , when considering military vehicles concealed in a forest.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje