Probabilistic satellite image fusion

Farid Flitti; Mohammed Bennamoun; Du Huynh; Amine Bermak; Christophe Collet

doi:10.1007/978-3-642-03767-2_50

Probabilistic satellite image fusion

Farid Flitti^*, Mohammed Bennamoun, Du Huynh, Amine Bermak, Christophe Collet

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Remote sensing satellite images play an important role in many applications such as environment and agriculture lands monitoring. In such images the scene is usually observed with different modalities, e.g. wavelengths. Image Fusion is an important analysis tool that summarizes the available information in a unique composite image. This paper proposes a new transform domain image fusion (IF) algorithm based on a hierarchical vector hidden Markov model (HHMM) and the mixture of probabilistic principal component analysers. Results on real Landsat images, quantified subjectively and using objective measures, are very satisfactory.

Original language	English
Title of host publication	Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Pages	410-418
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-03767-2_50
Publication status	Published - 2009
Externally published	Yes
Event	13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany Duration: 2 Sept 2009 → 4 Sept 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5702 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009
Country/Territory	Germany
City	Munster
Period	2/09/09 → 4/09/09

Access to Document

10.1007/978-3-642-03767-2_50

Cite this

Flitti, F., Bennamoun, M., Huynh, D., Bermak, A., & Collet, C. (2009). Probabilistic satellite image fusion. In Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings (pp. 410-418). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5702 LNCS). https://doi.org/10.1007/978-3-642-03767-2_50

@inproceedings{75f0a9baedee46e389fae950908b3975,

title = "Probabilistic satellite image fusion",

abstract = "Remote sensing satellite images play an important role in many applications such as environment and agriculture lands monitoring. In such images the scene is usually observed with different modalities, e.g. wavelengths. Image Fusion is an important analysis tool that summarizes the available information in a unique composite image. This paper proposes a new transform domain image fusion (IF) algorithm based on a hierarchical vector hidden Markov model (HHMM) and the mixture of probabilistic principal component analysers. Results on real Landsat images, quantified subjectively and using objective measures, are very satisfactory.",

author = "Farid Flitti and Mohammed Bennamoun and Du Huynh and Amine Bermak and Christophe Collet",

year = "2009",

doi = "10.1007/978-3-642-03767-2_50",

language = "English",

isbn = "3642037666",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "410--418",

booktitle = "Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings",

note = "13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 ; Conference date: 02-09-2009 Through 04-09-2009",

}

Flitti, F, Bennamoun, M, Huynh, D, Bermak, A & Collet, C 2009, Probabilistic satellite image fusion. in Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5702 LNCS, pp. 410-418, 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009, Munster, Germany, 2/09/09. https://doi.org/10.1007/978-3-642-03767-2_50

Probabilistic satellite image fusion. / Flitti, Farid; Bennamoun, Mohammed; Huynh, Du et al.
Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. 2009. p. 410-418 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5702 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Probabilistic satellite image fusion

AU - Flitti, Farid

AU - Bennamoun, Mohammed

AU - Huynh, Du

AU - Bermak, Amine

AU - Collet, Christophe

PY - 2009

Y1 - 2009

N2 - Remote sensing satellite images play an important role in many applications such as environment and agriculture lands monitoring. In such images the scene is usually observed with different modalities, e.g. wavelengths. Image Fusion is an important analysis tool that summarizes the available information in a unique composite image. This paper proposes a new transform domain image fusion (IF) algorithm based on a hierarchical vector hidden Markov model (HHMM) and the mixture of probabilistic principal component analysers. Results on real Landsat images, quantified subjectively and using objective measures, are very satisfactory.

AB - Remote sensing satellite images play an important role in many applications such as environment and agriculture lands monitoring. In such images the scene is usually observed with different modalities, e.g. wavelengths. Image Fusion is an important analysis tool that summarizes the available information in a unique composite image. This paper proposes a new transform domain image fusion (IF) algorithm based on a hierarchical vector hidden Markov model (HHMM) and the mixture of probabilistic principal component analysers. Results on real Landsat images, quantified subjectively and using objective measures, are very satisfactory.

UR - http://www.scopus.com/inward/record.url?scp=70349471010&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-03767-2_50

DO - 10.1007/978-3-642-03767-2_50

M3 - Conference contribution

AN - SCOPUS:70349471010

SN - 3642037666

SN - 9783642037665

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 410

EP - 418

BT - Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings

T2 - 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009

Y2 - 2 September 2009 through 4 September 2009

ER -

Flitti F, Bennamoun M, Huynh D, Bermak A, Collet C. Probabilistic satellite image fusion. In Computer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings. 2009. p. 410-418. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-03767-2_50

Probabilistic satellite image fusion

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this