False Alarm Reduction in Wavelength-Resolution SAR Change Detection Using Adaptive Noise Canceler

2017 ◽  
Vol 55 (1) ◽  
pp. 591-599 ◽  
Author(s):  
Viet Thuy Vu ◽  
Mats I. Pettersson ◽  
Renato Machado ◽  
Patrik Dammert ◽  
Hans Hellsten
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
Wavelength Resolution ◽  
Adaptive Noise ◽  
Alarm Reduction ◽  
Noise Canceler

Discrimination Algorithm for False Alarm Reduction in SAR Incoherent Change Detection

2019 ◽  
Author(s):  
Alexandre Campos ◽  
Ricardo Molin ◽  
Mats Pettersson ◽  
Renato Machado
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
Alarm Reduction

scholarly journals Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2008 ◽  
Author(s):  
Bruna G. Palm ◽  
Dimas I. Alves ◽  
Mats I. Pettersson ◽  
Viet T. Vu ◽  
Renato Machado ◽  
...  
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Reference Image ◽  
Sar Images ◽  
Image Stack ◽  
Military Vehicles ◽  
Wavelength Resolution

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.

scholarly journals A Wavelength-Resolution SAR Change Detection Method Based on Image Stack through Robust Principal Component Analysis

2021 ◽  
Vol 13 (5) ◽  
pp. 833
Author(s):  
Lucas P. Ramos ◽  
Alexandre B. Campos ◽  
Christofer Schwartz ◽  
Leonardo T. Duarte ◽  
Dimas I. Alves ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Change Detection ◽  
False Alarm ◽  
Detection Method ◽  
Principal Component ◽  
Robust Principal Component Analysis ◽  
Sar Images ◽  
Image Stack ◽  
Wavelength Resolution ◽  
Reference Images

Recently, it was demonstrated that low-frequency wavelength-resolution synthetic aperture radar (SAR) images could be considered to follow an additive mixing model due to their backscatter characteristics. This simplification allows for the use of source separation methods, such as robust principal component analysis (RPCA) via principal component pursuit (PCP), for detecting changes in those images. In this manuscript, a change detection method for wavelength-resolution SAR images based on image stack through RPCA is proposed. The method aims to explore both the temporal and flight heading diversity of a set of wavelength-resolution multitemporal SAR images in order to detect concealed targets in forestry areas. A heuristic based on three rules for better exploring the RPCA results is introduced, and a new configurable parameter for false alarm reduction based on the analysis of image windows is proposed. The method is evaluated using real data obtained from measurements of the ultrawideband (UWB) very high-frequency (VHF) SAR system CARABAS-II. Experiments for stacks of four and seven reference images are conducted, and the use of reference images acquired with different flight headings is explored. The results indicate that a gain in performance can be achieved by using large image stacks containing, at least, one image of each possible flight heading of the data set, which can result in a probability of detection (PD) above 99% for a false alarm rate (FAR) as low as one false alarm per three square kilometers. Furthermore, it is demonstrated that high PD and low FAR can be achieved, also considering images from similar flight headings as reference images.

A Constant False Alarm Rate-(CFAR) Based Change Detection Approach to Helicopter Diagnostics

2008 ◽  
Author(s):  
Kenneth Ranney ◽  
Hiralal Khatri ◽  
Jerry Silvious ◽  
Kwok Tom ◽  
Romeo del Rosario
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Detection Approach

scholarly journals Neyman-Pearson Criterion-Based Change Detection Methods for Wavelength-Resolution SAR Image Stacks

2021 ◽  
pp. 1-5
Author(s):  
Dimas I. Alves ◽  
Cristian Muller ◽  
Bruna G. Palm ◽  
Mats I. Pettersson ◽  
Viet T. Vu ◽  
...  
Keyword(s):  
Change Detection ◽  
Detection Methods ◽  
Sar Image ◽  
Pearson Criterion ◽  
Wavelength Resolution
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