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CORR
2012
Springer
225views Education» more  CORR 2012»
12 years 5 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
SIAMIS
2011
13 years 29 days ago
Level Set Based Multispectral Segmentation with Corners
In this paper we propose an active contour model for segmentation based on the Chan-Vese model. The new model can capture inherent sharp features, i.e., the sharp corners of object...
Wenhua Gao, Andrea L. Bertozzi
IGARSS
2010
13 years 8 months ago
Recent developments in sparse hyperspectral unmixing
This paper explores the applicability of new sparse algorithms to perform spectral unmixing of hyperspectral images using available spectral libraries instead of resorting to well...
Marian-Daniel Iordache, Antonio J. Plaza, Jos&eacu...
ICIP
2010
IEEE
13 years 8 months ago
Hyper-DEMIX: Blind source separation of hyperspectral images using local ML estimates
We propose a new method to unmix hyperspectral images. Our method exploits the structure of the material abundance maps by assuming that in some regions of the spatial dimension, ...
Simon Arberet
ICIP
2010
IEEE
13 years 8 months ago
Hyperspectral image segmentation and unmixing using hidden Markov trees
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors. We hypothesize that hy...
Roni Mittelman, Alfred O. Hero III
TIP
2008
131views more  TIP 2008»
13 years 10 months ago
Hyperspectral Image Compression: Adapting SPIHT and EZW to Anisotropic 3-D Wavelet Coding
Abstract--Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability...
Emmanuel Christophe, Corinne Mailhes, Pierre Duham...
KES
2008
Springer
13 years 10 months ago
Classification of Hyperspectral Images Compressed through 3D-JPEG2000
Abstract. Classification of hyperspectral images is paramount to an increasing number of user applications. With the advent of more powerful technology, sensed images demand for la...
Ian Blanes, Alaitz Zabala, Gerard Moré, Xav...
ESANN
2006
13 years 11 months ago
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
HAIS
2010
Springer
14 years 2 months ago
On the Use of a Hybrid Approach to Contrast Endmember Induction Algorithms
Abstract. In remote sensing hyperspectral image processing, identifying the constituent spectra (endmembers) of the materials in the image is a key procedure for further analysis. ...
Miguel A. Veganzones, Carmen Hernández
SBCCI
2003
ACM
129views VLSI» more  SBCCI 2003»
14 years 3 months ago
Hyperspectral Images Clustering on Reconfigurable Hardware Using the K-Means Algorithm
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...
Abel Guilhermino S. Filho, Alejandro César ...