A SEMANTIC-BASED MULTILEVEL APPROACH TO CHANGE DETECTION IN VERY HIGH GEOMETRICAL RESOLUTION MULTITE...
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A SEMANTIC-BASED MULTILEVEL APPROACH TO CHANGE DETECTION IN VERY HIGH GEOMETRICAL RESOLUTION MULTITEMPORAL IMAGES. Lorenzo Bruzzone Francesca Bovolo. E-mail: [email protected] Web page: http://rslab.disi.unitn.it. Outline. Introduction on change detection in VHR images. 1.

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Lorenzo bruzzone francesca bovolo

A SEMANTIC-BASED MULTILEVEL APPROACH TO CHANGE DETECTION IN VERY HIGH GEOMETRICAL RESOLUTION MULTITEMPORAL IMAGES

Lorenzo Bruzzone

Francesca Bovolo

E-mail: [email protected]

Web page: http://rslab.disi.unitn.it


Outline

Outline

Introduction on change detection in VHR images

1

General approach to change detection in VHR images

2

Illustration on the use of the approach for the solution of a specific change detection problem

3

4

Experimental results

Conclusion

5

Lorenzo Bruzzone, Francesca Bovolo


Introduction change detection in vhr images

Introduction: Change Detection in VHR Images

  • Main assumption: unsupervised change-detection techniques generally assume that multitemporal images are similar to each other except for the presence of changes occurred on the ground.

    Problems: This assumption is seldom satisfied in VHR images due to:

    • the complexity of the objects present in the scene (which may show different spectral behaviors at two different dates even if their semantic meaning does not change);

    • the differences in the acquisition conditions (e.g., sensor acquisition geometry, atmospheric and sunlight conditions, etc.).

Lorenzo Bruzzone, Francesca Bovolo


Lorenzo bruzzone francesca bovolo

Introduction: Change Detection in VHR Images

October 2005

July 2006

Quickbird images acquired on a portion of the city of Trento (Italy)

Lorenzo Bruzzone, Francesca Bovolo

4


Aim of the work

Aim of the Work

  • We propose a general top-down approach to the definition of the architecture of change detection methods for multitemporal VHR images.

  • The proposed approach:

    • explicitly models the presence of different radiometricchanges on the basis of the properties of the considered images

    • extracts the semantic meaning of changes;

    • identifies changes of interest with strategies designed on the basis of the specific application;

    • exploits the intrinsic multiscale properties of the objects and the high spatial correlation between pixels in a neighborhood.

Lorenzo Bruzzone, Francesca Bovolo

5


Lorenzo bruzzone francesca bovolo

Proposed Approach: Architecture Design

Multitemporal data set

Auxiliary

information

Identification of the tree of

radiometric changes

Detection of all

radiometric changes

Selection of the

strategy for detecting

changes of interest

Direct extraction of

changes of interest

Differential extraction of changes

of interest by cancellation

Detection of the changes of interest

Refined detection of the radiometric

change of interest

Change detection map

Lorenzo Bruzzone, Francesca Bovolo

6


Lorenzo bruzzone francesca bovolo

Identification of the Tree of Radiometric Changes

Radiometric

Changes(Wrad)

Changes due to acquisition conditions (WAcq)

Changes occurred on the ground (WGrd)

Differences in acquisition system (WSys)

Natural disasters (WDis)

Differences in atmospheric conditions (WAtm)

Anthropic activity (WAnt)

Vegetation

Phenology (Wveg)

Type of sensor

Sensor acquisition mode

Environmental conditions (WEnv)

Sensor view angle

Seasonal effects

Lorenzo Bruzzone, Francesca Bovolo

7


Lorenzo bruzzone francesca bovolo

Proposed Approach: Architecture Design

Multitemporal data set

Auxiliary

information

Identification of the tree

of radiometric changes

Change Vector Analysis,

Context-sensitive

techniques, etc.

Detection of all

radiometric changes

Selection of the

strategy for detecting

changes of interest

Direct extraction of

changes of interest

Differential extraction of changes

of interest by cancellation

Detection of the changes of interest

Refined detection of the radiometric

change of interest

Change detection map

Lorenzo Bruzzone, Francesca Bovolo

8


Lorenzo bruzzone francesca bovolo

Detection of Changes of Interest

Differential detection by cancellation

Direct detection of changes of interest

X1

X1

X2

X2

Detection of

radiometric changes

Detection of

change of interest 1

Detection of

change of interest K

Non-relevant

change 1

Non-relevant

change 2

Non-relevant

change N

-

-

-

+

+

+

+

+

Refined detection of the

radiometric change of interest

Map of changes

Map of changes

Lorenzo Bruzzone, Francesca Bovolo

9


Lorenzo bruzzone francesca bovolo

Multilevel Architecture: Semantic of Changes

Object Meta-level (o)

O1

O2

O

j=1,…,Jo

Classification map, object map,…

Primitive Meta-level (p)

P1

P2

P

Meta-levels

fusion

j=1,…,Jp

Geometric or statistic primitives

Map of a specific

Radiometric change

Pixel Meta-level (px)

X1

X2

D

j=1,…,Jpx

Pixel radiometry

Lorenzo Bruzzone, Francesca Bovolo


Lorenzo bruzzone francesca bovolo

Data Set Description

Study area: South part of Trento (Italy).

Multitemporal data set: portion (380×430 pixels) of two images acquired by the Quickbird satellite in October 2004 and July 2006.

Causes of Change:changes on the ground, seasonal changes, registration noise.

October 2004

July 2006

Reference Map


Lorenzo bruzzone francesca bovolo

Proposed Approach: Architecture Design

Multitemporal data set

Auxiliary

information

Identification of the tree of

radiometric changes

Change Vector Analysis,

Context-sensitive

techniques, etc.

Detection of all

radiometric changes

Selection of the

strategy for detecting

changes of interest

Direct extraction of

changes of interest

Differential extraction of changes

of interest by cancellation

Detection of the changes of interest

Refined detection of the radiometric

change of interest

Change detection map

Lorenzo Bruzzone, Francesca Bovolo

12


Identification of the tree of radiometric changes

Identification of the Tree of Radiometric Changes

WRad

WSys

WGrd

wsh

wrn

WVeg

WAnt

Shadow

changes

wgl

wat

wb

Registration

noise

Grassland

Apple

trees

New

buildings

Lorenzo Bruzzone, Francesca Bovolo


Changes tree and detection strategy

Changes Tree and Detection Strategy

Differential detection by cancellation

Identification of the tree of

radiometric changes

X1

X2

Detection of radiometric

Changes (CVA)

WRad

WSys

WGrd

Detection

of wsh

Detection

of wrn

-

-

+

+

wsh

wrn

Refined detection of WGrd

Shadow

changes

Registration

noise

Map of changes

Lorenzo Bruzzone, Francesca Bovolo


Multilevel representation of radiometric changes

Multilevel Representation of Radiometric Changes

S. Marchesi, F. Bovolo, L. Bruzzone, “A Context-Sensitive Technique Robust to Registration Noise for Change Detection in VHR Multispectral Images”, IEEE Transactions on Image Processing, Vol. 19, pp. 1877-1889, 2010.

Registration

noise map

Primitive Meta-level (p)

Segmentation map

F. Bovolo, “A Multilevel Parcel-Based Approach to Change Detection in Very High Resolution Multitemporal Images,” IEEE Geoscience and Remote Sensing Letters, Vol. 6, No. 1, pp. 33-37, January 2009.

Parcel map

Shadow Index

V. J. D. Tsai, "A comparative study on shadow compensation of color aerial images in invariant color models," IEEE Trans. Geosci. Remote Sens., vol. 44, pp. 1661-1671, 2006.

Shadow change

index

Pixel Meta-level (px)

X1

X2

L. Bruzzone and D. Fernández-Prieto, "Automatic Analysis of the Difference Image for Unsupervised Change detection," IEEE Trans. Geosci. Rem. Sens., vol. 38, pp. 1170-1182, 2000.

Magnitude of

multispectral

change vectors

Image radiometry

Lorenzo Bruzzone, Francesca Bovolo

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Lorenzo bruzzone francesca bovolo

Proposed Approach: Block Scheme

Multiscale analysis

for wrn detection

Shadow

detection

Comparison

wsh

detection

-

-

Shadowchange

index

+

Shadowindex

CVA

Wrad

detection

Change-detection

map

X1

Magnitudeof

multispectral

changevectors

W={Wnc, WGrd}

Parcel

detection

X2

Lorenzo Bruzzone, Francesca Bovolo

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Lorenzo bruzzone francesca bovolo

Experimental Results

Overall change detection accuracy (%)

95

93.91

91.56

90

90.86

85

80

CVA

Pixel-based

CVA

parcel-based

Proposed

method

Marzo 2011


Lorenzo bruzzone francesca bovolo

Experimental Results

October 2005

July 2006

Reference Map

Change Detection map

CVA parcel based

Change detection map

Proposed approach

Marzo 2011


Lorenzo bruzzone francesca bovolo

Conclusion

  • We presented a general top-down approach to the definition of the architecture of change detection methods for multitemporal VHR images.

  • The main concepts exploited for the definition of the change detection architecture are:

    • Modeling the types of radiometric changes expected between images;

    • Extracting the semantic meaning from radiometric changes.

  • The approach proposed includes:

    • Direct detection of changes of interest or differential cancellation of uninteresting radiometric changes;

    • Multilevel and context-sensitive techniques;

    • Iterative strategy.

  • The approach has been successfully applied to the definition of aneffective architecture for change detection between Quickbird images in different application scenarios.

  • Lorenzo Bruzzone, Francesca Bovolo


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