Optimum Method Selection for Resolution Enhancement of Hyperspectral Imagery

[1]  Chein-I Chang,et al.  Weighted abundance-constrained linear spectral mixture analysis , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[2]  William T. Freeman,et al.  Example-Based Super-Resolution , 2002, IEEE Computer Graphics and Applications.

[3]  Chein-I Chang,et al.  Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[4]  Martin Brown,et al.  Support vector machines for optimal classification and spectral unmixing , 1999 .

[5]  Chein-I Chang,et al.  Constrained subpixel target detection for remotely sensed imagery , 2000, IEEE Trans. Geosci. Remote. Sens..

[6]  Russell C. Hardie,et al.  Application of the stochastic mixing model to hyperspectral resolution enhancement , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Russell C. Hardie,et al.  MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor , 2004, IEEE Transactions on Image Processing.

[8]  Russell C. Hardie,et al.  Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Jincheng Gao,et al.  The effect of solar illumination angle and sensor view angle on observed patterns of spatial structure in tallgrass prairie , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Gary A. Shaw,et al.  Hyperspectral Image Processing for Automatic Target Detection Applications , 2003 .

[11]  Masatoshi Okutomi,et al.  A fast algorithm for reconstruction-based superresolution and evaluation of its accuracy , 2007 .

[12]  Rama Chellappa,et al.  Hybrid Detectors for Subpixel Targets , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Yao Lu,et al.  Super‐resolution of the undersampled and subpixel shifted image sequence by a neural network , 2004, Int. J. Imaging Syst. Technol..

[14]  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..

[15]  Aggelos K. Katsaggelos,et al.  High‐resolution images from compressed low‐resolution video: Motion estimation and observable pixels , 2004, Int. J. Imaging Syst. Technol..

[16]  G. J. Owirka,et al.  Automatic target recognition using enhanced resolution SAR data , 1999 .

[17]  John R. Schott,et al.  Application of Spectral Mixture Analysis and Image Fusion Techniques for Image Sharpening , 1998 .

[18]  Thomas L. Ainsworth,et al.  Exploiting manifold geometry in hyperspectral imagery , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[19]  F. J. García-Haro,et al.  Linear spectral mixture modelling to estimate vegetation amount from optical spectral data , 1996 .

[20]  Brian S. Penn,et al.  Using simulated annealing to obtain optimal linear end-member mixtures of hyperspectral data , 2002 .

[21]  Yücel Altunbasak,et al.  Super-resolution reconstruction of hyperspectral images , 2005 .

[22]  J. Schott,et al.  Resolution enhancement of multispectral image data to improve classification accuracy , 1993 .

[23]  Euncheol Choi,et al.  Super‐resolution approach to overcome physical limitations of imaging sensors: An overview , 2004, Int. J. Imaging Syst. Technol..

[24]  Sen Jia,et al.  Spectral and Spatial Complexity-Based Hyperspectral Unmixing , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[25]  Michael E. Winter,et al.  Physics-based resolution enhancement of hyperspectral data , 2002, SPIE Defense + Commercial Sensing.

[26]  Paul E. Johnson,et al.  Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 Site , 1986 .

[27]  Ryuei Nishii,et al.  Enhancement of low spatial resolution image based on high resolution-bands , 1996, IEEE Trans. Geosci. Remote. Sens..

[28]  Jorge Núñez,et al.  Super-Resolution of Remotely Sensed Images With Variable-Pixel Linear Reconstruction , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Takeo Kanade,et al.  Limits on Super-Resolution and How to Break Them , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Jing Wang,et al.  Applications of Independent Component Analysis in Endmember Extraction and Abundance Quantification for Hyperspectral Imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Michael Elad,et al.  Advances and challenges in super‐resolution , 2004, Int. J. Imaging Syst. Technol..

[32]  Bing Zeng,et al.  A new three-step search algorithm for block motion estimation , 1994, IEEE Trans. Circuits Syst. Video Technol..

[33]  S. Sandmeier,et al.  The potential of hyperspectral bidirectional reflectance distribution function data for grass canopy characterization , 1999 .

[34]  Hugh G. Lewis,et al.  Super-resolution target identification from remotely sensed images using a Hopfield neural network , 2001, IEEE Trans. Geosci. Remote. Sens..

[35]  Ye Zhang,et al.  Super-Resolution Challenges in Hyperspectral Imagery , 2008 .

[36]  John R. Schott,et al.  Evaluation of Two Applications of Spectral Mixing Models to Image Fusion , 2000 .

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

[38]  Bjørn K. Alsberg,et al.  Superresolution of hyperspectral images , 2006 .

[39]  Peyman Milanfar,et al.  Statistical performance analysis of super-resolution , 2006, IEEE Transactions on Image Processing.

[40]  Martin Vetterli,et al.  Reconstruction of irregularly sampled discrete-time bandlimited signals with unknown sampling locations , 2000, IEEE Trans. Signal Process..

[41]  Lieven Verbeke,et al.  Sub-pixel mapping and sub-pixel sharpening using neural network predicted wavelet coefficients , 2004 .

[42]  G. Foody.  Sharpening fuzzy classification output to refine the representation of sub-pixel land cover distribution , 1998 .

[43]  Hugh G. Lewis,et al.  Superresolution mapping using a hopfield neural network with fused images , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[44]  Huifang Li,et al.  Fast MAP-based multiframe super-resolution image reconstruction , 2005, Image Vis. Comput..

[45]  P. Atkinson,et al.  Mapping sub-pixel proportional land cover with AVHRR imagery , 1997 .

[46]  E. M. Winter,et al.  Anomaly detection from hyperspectral imagery , 2002, IEEE Signal Process. Mag..

[47]  Lorenzo Bruzzone,et al.  A Model-Based Approach to Multiresolution Fusion in Remotely Sensed Images , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[48]  J. C. Price,et al.  Combining panchromatic and multispectral imagery dual resolution satellite instruments , 1987 .

[49]  Ye Zhang,et al.  Integration of Spatial–Spectral Information for Resolution Enhancement in Hyperspectral Images , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[50]  Myeong-Ryong Nam,et al.  Fusion of multispectral and panchromatic Satellite images using the curvelet transform , 2005, IEEE Geoscience and Remote Sensing Letters.

[51]  Chein-I Chang,et al.  Linear spectral random mixture analysis for hyperspectral imagery , 2002, IEEE Trans. Geosci. Remote. Sens..