Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree

被引：35

作者：

Alonso-Gonzalez, Alberto ^{[1
]}

Valero, Silvia ^{[1
,2
]}

Chanussot, Jocelyn ^{[2
]}

Lopez-Martinez, Carlos ^{[1
]}

Salembier, Philippe ^{[1
]}

机构：

[1] Tech Univ Catalonia, Signal Theory & Commun Dept, Barcelona 08034, Spain

[2] Grenoble Inst Technol INPG, Grenoble Images Speech Signals & Automat Lab, F-38016 Grenoble, France

来源：

PROCEEDINGS OF THE IEEE | 2013年 / 101卷 / 03期

关键词：

Binary partition tree (BPT); classification; filtering; hyperspectral images; segmentation; synthetic aperture radar (SAR) images; CLASSIFICATION; MODEL; SEGMENTATION; INTENSITY;

D O I：

10.1109/JPROC.2012.2205209

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The current increase of spatial as well as spectral resolutions of modern remote sensing sensors represents a real opportunity for many practical applications but also generates important challenges in terms of image processing. In particular, the spatial correlation between pixels and/or the spectral correlation between spectral bands of a given pixel cannot be ignored. The traditional pixel-based representation of images does not facilitate the handling of these correlations. In this paper, we discuss the interest of a particular hierarchical region-based representation of images based on binary partition tree (BPT). This representation approach is very flexible as it can be applied to any type of image. Here both optical and radar images will be discussed. Moreover, once the image representation is computed, it can be used for many different applications. Filtering, segmentation, and classification will be detailed in this paper. In all cases, the interest of the BPT representation over the classical pixel-based representation will be highlighted.

引用

页码：723 / 747

页数：25

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