1 intro ElabImRad - Dipartimento Infocominfocom.uniroma1.it/~pier/ElabImR/materiale_didattico_file/1_intro... · Elaborazione delle immagini radar P. Lombardo – Dip. INFOCOM, Univ

Elaborazione delle immagini radar

P. Lombardo – Dip. INFOCOM, Univ. di Roma “La Sapienza” INTRO – 1

Elaborazione delle Immagini Radar

Pierfrancesco Lombardo

– Tel: 06- 44585472 (interno 25-472)– E-mail: [email protected]



•Parte I: Formazione delle immagini Radar

- il principio di formazione delle immagini SAR- la migrazione in distanza e le tecniche di compensazione- moto della piattaforma, stima del centroide Doppler e autofocus- calibrazione e ortorettificazione delle immagini SAR

•Parte II: Estrazione di informazioni dalle immagini Radar

- statistica delle immagini SAR e speckle noise- tecniche di despeckling- tecniche di segmentazione per immagini SAR- tecniche di classificazione di immagini SAR

•Parte III: Elaborazione delle immagini SAR multi-dimensionali

- elaborazione di immagini SAR polarimetriche- elaborazione di immagini SAR multitemporali & change detection- data fusion con immagini raccolte da altri sensori (SAR & opical/IR)- principi di interferometria SAR- rivelazione di bersagli in immagini SAR

Programma del corso



Parte I: il principio di formazione delle immagini SAR

R0

h

R(x)

x negative Doppler

positive Doppler

R0h

R(x)

x

Radar ad Apertura SinteticaSynthetic Aperture Radar (SAR)

Frequenza Doppler funzione del tempo



From:C.J. Oliver, S. Quegan,”Understanding Synthetic Aperture Radar Images”, Artech House, 1998

Parte I: Esempio di immagine SAR da aereo



Parte I: Esempio di immagine SAR da UAV

www.fas.org

TESAR

Pentagon



Parte I: Esempio di immagine SAR da Satellite

• SIR-C images of the town of Pavia• C and L band• Fully polarimetric (Standard MLC format)• Incidence angle at image center 44.4°

N

• Ground truth from a Technical Regional Map:Water

Agricultural areaUrban area



∑=

=N

k

ik

i keAAe1

φφ

Parte II: lo speckle nelle immagini SAR



Parte II: tecniche di despeckling



Parte II: tecniche di segmentazione



2. Minimum Distance calculations: Each pixel is associated with closest mean

Parte II: Image Classification

.

Band 1

Ban

d 2

..... . ..

..

.. .

.

.

.

.

...

. .... .

..

..

.. ....

.. ..

. .. . .

...... .

.. ......

..... . .

..

.

.. ..

. . ...... . .

. .

.

. .

.

Cluster Means1. Means are initialized along diagonal

3. New mean calculated for each cluster and means migrate to new locations

1

2

4. Iterations continue until convergence or maximum iterations is reached

5. Each cluster associated with a value. Each pixel given this value

2



Parte II: Supervised Classification



Parte III: Change Detection

• Requires temporal datasets1987 1997



Parte III: Change Detection (II)

Changes automatically

identified



From:C.J. Oliver, S. Quegan,”Understanding Synthetic Aperture Radar Images”, Artech House, 1998

Parte III: Elaborazione di imagini SAR polarimetriche



This is the first calibrated, multi-frequency, multi-polarization spaceborne radar image of the seasonal sea-ice cover in the Weddell Sea, Antarctica. The multi-channel data provide scientists with details about the ice pack they cannot see any other way and indicates that the large expanse of sea-ice is, in fact, comprised of many smaller rounded ice floes, shown in blue-gray. These data are particularly useful in helping scientists estimate the thickness of the ice cover which is often extremely difficult to measure with other remote sensing systems. This image is produced by overlaying three channels of radar data in the following colors: red (C-band, HH-polarization), green (L-band HV-polarization), and blue (L-band, HH-polarization).

From: NASA/JPL ImagingRadar Home Page

http://southprt.jpl.nasa.gov

Parte III: Esempio diWeddel Sea-Ice Monitoring SIR-C



SIR-C Oberpfaffenhofen



Parte III: SIR-C Multipol SAR image of Land cover



SIR-C Flevoland



Parte III: SIR-C Image of urban and agricultural areas



Vesuvius, Italy

Due to the violent eruptive style and proximity to populated areas, Vesuvius has been named by the international scientific community as one of fifteen Decade Volcanoes which are being intensively studied during the 1990s. This image was acquired on April 15, 1994 by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the Space Shuttle Endeavour. SIR-C/X-SAR, a joint mission of the German, Italian and the United States space agencies, is part of NASA's Mission to Planet Earth.

Parte III: Mt. Vesuvius - SIR-C polarimetric



Parte III: Data Fusion

SAR

Day 1

Day 2

Multiband opticalOptical images provide

good classification accuracies, but

multitemporal sequences are unlikely to be available (depends on atmospheric

conditions). Consequently, it is difficult to identify changes in the observed

area

Single-channel SAR images do not yield satisfactory classification accuracies, but the

availability of long sequences allows to identify changes

Multisensor image fusionto retain

the advantages of both

Multisensor image fusionto retain

the advantages of both



Agricultural and forested area in Northern Italy Agricultural and forested area in Northern Italy –– images collected in May 1994images collected in May 1994

ERS PRIERS PRI

LandsatLandsat TM band 5TM band 5




7

6

5

4

3

2

1

classification results ground truth

classes 2, 3 and 5 correctly classified




Parte III: Interferometria SAR

www.sandia.gov

The Rapid Terrain Visualization (RTV) interferometric synthetic aperture radar sensor was designed and developed by Sandia National Laboratories for the Joint Precision Demonstration Project Office of the United States Army (Intelligence, Electronic Warfare & Sensors PEO). This radar provides the ability to generate highly accurate map products in real-time, including digital elevation models (DEMs), orthorectified SAR images, as well as a measure of the data quality.



Parte III: Target detection and recognition



Parte III: Target discrimination

Clutter scene from the MSTAR database



Parte III: Targets embedded in non-homogeneous clutter

PR detections

Two-parameter detections

Chip targets inserted intoclutter scenes

Performance of the Power Ratio and the

two-parameter schemes



SAR images of the seaSAR images of the sea

Quick look ERS-2 images (a)

(c)

(c)

(b)

(d)

(e)

Low resolution SIR-C image

(f)

Parte III: Ship Target ATR



dual antennaalong track

Parte III: SAR moving target imaging



From FFM-FGANJ. Ender

AntennaArray

Parte III: SAR moving target detection

Documents

1 intro ElabImRad - Dipartimento Infocominfocom.uniroma1.it/~pier/ElabImR/materiale_didattico_file/1_intro... · Elaborazione delle immagini radar P. Lombardo – Dip. INFOCOM, Univ