Sparsity and Structure in Hyperspectral Imaging

[1]  Shahram Shirani,et al.  CMOS Image Sensor With Area-Efficient Block-Based Compressive Sensing , 2015, IEEE Sensors Journal.

[2]  Henry Arguello,et al.  Compressive Coded Aperture Spectral Imaging: An Introduction , 2014, IEEE Signal Processing Magazine.

[3]  Adrian Stern,et al.  Compressive hyperspectral imaging by random separable projections in both the spatial and the spectral domains. , 2013, Applied optics.

[4]  James E. Fowler,et al.  Integration of Spectral–Spatial Information for Hyperspectral Image Reconstruction From Compressive Random Projections , 2013, IEEE Geoscience and Remote Sensing Letters.

[5]  Pierre Vandergheynst,et al.  Compressive Source Separation: Theory and Methods for Hyperspectral Imaging , 2012, IEEE Transactions on Image Processing.

[6]  Emmanuel J. Candès,et al.  On the Fundamental Limits of Adaptive Sensing , 2011, IEEE Transactions on Information Theory.

[7]  Abbas El Gamal,et al.  CMOS Image Sensor With Per-Column ΣΔ ADC and Programmable Compressed Sensing , 2013, IEEE Journal of Solid-State Circuits.

[8]  Karen O. Egiazarian,et al.  Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction , 2013, IEEE Transactions on Image Processing.

[9]  Jinzhu Jia,et al.  Preconditioning to comply with the Irrepresentable Condition , 2012, 1208.5584.

[10]  Kun Liu,et al.  CMOS low data rate imaging method based on compressed sensing , 2012 .

[11]  Rebecca Willett,et al.  Poisson Noise Reduction with Non-local PCA , 2012, Journal of Mathematical Imaging and Vision.

[12]  Antonio J. Plaza,et al.  Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[13]  Rebecca Willett,et al.  Target detection performance bounds in compressive imaging , 2011, EURASIP Journal on Advances in Signal Processing.

[14]  Richard G. Baraniuk,et al.  The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range , 2011, IEEE Transactions on Signal Processing.

[15]  Qian Du,et al.  Anomaly Detection and Reconstruction From Random Projections , 2012, IEEE Transactions on Image Processing.

[16]  Richard G. Baraniuk,et al.  Democracy in Action: Quantization, Saturation, and Compressive Sensing , 2011 .

[17]  Po-Ling Loh,et al.  High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity , 2011, NIPS.

[18]  Yonina C. Eldar,et al.  Structured Compressed Sensing: From Theory to Applications , 2011, IEEE Transactions on Signal Processing.

[19]  Bruno A. Olshausen,et al.  Learning Sparse Codes for Hyperspectral Imagery , 2011, IEEE Journal of Selected Topics in Signal Processing.

[20]  Emmanuel J. Candès,et al.  How well can we estimate a sparse vector? , 2011, ArXiv.

[21]  A. Robert Calderbank,et al.  Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise , 2010, IEEE Transactions on Signal Processing.

[22]  Trac D. Tran,et al.  Effects of linear projections on the performance of target detection and classification in hyperspectral imagery , 2011 .

[23]  Peter Z. G. Qian,et al.  Orthogonalizing Penalized Regression , 2011 .

[24]  Alessandro Foi,et al.  Optimal Inversion of the Anscombe Transformation in Low-Count Poisson Image Denoising , 2011, IEEE Transactions on Image Processing.

[25]  Rebecca Willett,et al.  Gradient projection for linearly constrained convex optimization in sparse signal recovery , 2010, 2010 IEEE International Conference on Image Processing.

[26]  Laurent Jacques,et al.  A (256×256) pixel 76.7mW CMOS imager/ compressor based on real-time In-pixel compressive sensing , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[27]  Stephen J. Wright,et al.  Computational Methods for Sparse Solution of Linear Inverse Problems , 2010, Proceedings of the IEEE.

[28]  Roummel F. Marcia,et al.  Compressed Sensing Performance Bounds Under Poisson Noise , 2009, IEEE Transactions on Signal Processing.

[29]  Deanna Needell,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.

[30]  James E. Fowler,et al.  Compressive-Projection Principal Component Analysis , 2009, IEEE Transactions on Image Processing.

[31]  Jianwei Ma,et al.  A Single-Pixel Imaging System for Remote Sensing by Two-Step Iterative Curvelet Thresholding , 2009, IEEE Geoscience and Remote Sensing Letters.

[32]  Richard G. Baraniuk,et al.  Random Projections of Smooth Manifolds , 2009, Found. Comput. Math..

[33]  Mike E. Davies,et al.  Iterative Hard Thresholding for Compressed Sensing , 2008, ArXiv.

[34]  Ashwin A. Wagadarikar,et al.  Single disperser design for coded aperture snapshot spectral imaging. , 2008, Applied optics.

[35]  Richard G. Baraniuk,et al.  Realization of Confocal and Hyperspectral Microscopy via Compressive Sensing , 2008 .

[36]  Richard G. Baraniuk,et al.  Compressive Sensing , 2008, Computer Vision, A Reference Guide.

[37]  Ting Sun,et al.  Single-pixel imaging via compressive sampling , 2008, IEEE Signal Process. Mag..

[38]  R. DeVore,et al.  A Simple Proof of the Restricted Isometry Property for Random Matrices , 2008 .

[39]  M E Gehm,et al.  Single-shot compressive spectral imaging with a dual-disperser architecture. , 2007, Optics express.

[40]  Richard G. Baraniuk,et al.  The smashed filter for compressive classification and target recognition , 2007, Electronic Imaging.

[41]  James E. Fowler,et al.  3D WAVELET-BASED COMPRESSION OF HYPERSPECTRAL IMAGERY , 2007 .

[42]  J. Haupt,et al.  Compressive Sampling for Signal Classification , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[43]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[44]  Dimitris G. Manolakis,et al.  Detection algorithms for hyperspectral imaging applications , 2002, IEEE Signal Process. Mag..

[45]  J. Shan,et al.  Principal Component Analysis for Hyperspectral Image Classification , 2002 .

[46]  Kwanghoon Sohn,et al.  Principal component analysis for compression of hyperspectral images , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[47]  Giovanni Poggi,et al.  Compression of multispectral images by three-dimensional SPIHT algorithm , 2000, IEEE Trans. Geosci. Remote. Sens..

[48]  Glenn Healey,et al.  Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions , 1999, IEEE Trans. Geosci. Remote. Sens..