Hyperspectral Image Compression Optimized for Spectral Unmixing
نویسندگان
چکیده
منابع مشابه
Spectral/Spatial Hyperspectral Image Compression
^Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland, Baltimore County, Baltimore, MD 21250 ^Computer Science Department, University of Extremadura Avda. de la Universidad s/n,10.071 Caceres, SPAIN ^Center for Space and Remote Sensing Research Graduate Institute of Space Science Department of Computer Science and...
متن کاملHyperspectral Eels Image Unmixing
Y. Altmann, N. Brun , N. Dobigeon , K. March, S. Moussaoui, O. Schneegans 1School of Engineering and Physical Sciences, Heriot-Watt University Earl Mountbatten Building, Riccarton, EH14 4AS, Edinburgh, U.K. Laboratoire de Physique des Solides, CNRS UMR 8502, Univ. Paris-Sud, Univ. Paris-Saclay Bât. 510, 91405 Orsay Cedex, France University of Toulouse, IRIT/INP-ENSEEIHT/TéSA 2 rue Charles Camic...
متن کاملAdvances in Hyperspectral and Multispectral Image Fusion and Spectral Unmixing
In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image. We assume that the two images are radiometrically corrected and geometric...
متن کاملHyperspectral Image Unmixing: Accounting For Wavelength Dependence∗
We introduce a method for hyperspectral unmixing that incorporates wavelength dependence in addition to spatial dependence. Spatial dependence is incorporated into the model using class labels on the pixels that is assigned using spectral clustering. Wavelength dependence is introduced by correlating the errors in the unmixing regression models. We propose a non-standard alternating direction m...
متن کاملHyperspectral Super-Resolution with Spectral Unmixing Constraints
Hyperspectral sensors capture a portion of the visible and near-infrared spectrum with many narrow spectral bands. This makes it possible to better discriminate objects based on their reflectance spectra and to derive more detailed object properties. For technical reasons, the high spectral resolution comes at the cost of lower spatial resolution. To mitigate that problem, one may combine such ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing
سال: 2016
ISSN: 0196-2892,1558-0644
DOI: 10.1109/tgrs.2016.2574757