Spectral Unmixing
Evaluation of stepwise spectral unmixing with HYDICE data
... The unmixing math is the same as the classic technique, with fewer endmembers to ...hierarchical unmixing did twice as well quantitatively and much better ...better unmixing without the lengthy ...
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Generation, validation, and application of abundance map reference data for spectral unmixing
... Reference data (“ground truth”) maps traditionally have been used to assess the accu- racy of imaging spectrometer classification algorithms. However, these reference data can be prohibitively expensive to produce, often ...
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Area Correlated Spectral Unmixing Based on Bayesian Nonnegative Matrix Factorization
... Spectral unmixing is a technique to extract a collection of pure spectra (called endmembers), by decomposing mixed pixels of a hyperspectral image and estimating the corresponding fractions (called as ...
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Enhancing spectral unmixing by considering the point spread function effect
... The method predicts the land cover proportions at a finer spatial resolution inversely from the original coarse proportions before predicting the enhanced proportions i.e., the final pre[r] ...
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Performance versus energy consumption of hyperspectral unmixing algorithms on multi core platforms
... biological threat detection, monitoring of oil spills and other types of chemical contamination [45-47]. In those cases, low-weight integrated components such as field programmable gate arrays (FPGAs) [48-50] and graph- ...
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Performance Evaluation of Various Hyperspectral Nonlinear Unmixing Algorithms
... appropriate unmixing process. Hyperspectral unmixing is an important process in many fields such as agriculture, geography and ...applications. Spectral unmixing is widely used for analyzing ...
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Hyperspectral Clustering and Unmixing of Satellite Imagery for the Study of Complex Society State Formation
... and unmixing algorithms are applied to hyperspectral Hyperion imagery over Oaxaca, ...on spectral over spatial exploitation for a land survey study, using open source tools to facilitate re- ...
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Hyperspectral Nonlinear Unmixing: Endmember Extracting Using Iterative Simplex CNN Method
... of spectral unmixing techniques are based on linear and nonlinear unmixing ...linear unmixing techniques assumes that in macroscopic pixel level, pure substances may present per pixel, but in ...
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FUSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES USING PCA AND UNMIXING TECHNIQUE
... the spectral angle mapper (SAM), the correlation coefficient (CC), the standard deviation (SD), the relative bias (RB), and the universal image quality index (UIQI) ...and spectral resolutions as well as ...
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Exploration of Unmixing and Classification of Hyperspectral Imagery
... spatial spectral preprocessing (SSPP) element, is utilized prior to spectral Unmixing and endmember ...as spectral statistics at preprocessing ...and spectral information has to be ...
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Alteration mineral mapping using Etm+ and hyperion remote sensing data at Bau Gold Field, Sarawak, Malaysia
... Abstract. The area under investigation is the Bau gold mining district in the State of Sarawak, East Malaysia, on the island of Borneo. It has tropical climate with limited bedrock exposures. Bau is a gold field similar ...
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Compressive Sampling Multispectral Imaging and Unmixing Method for Fluorescent Imaging
... zero. After de-noising, the NESTA reconstructed images are processed by the MVSA algorithm again, and the new unmixing spectra are shown in Fig. 5. Compared with the unmixing spectra shown in Fig. 4, it is ...
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Hapke-based computational method to enable unmixing of hyperspectral data of common salts
... Environmental scientists are currently assessing the ability of hyper-spectral remote sensing to detect, identify, and analyze natural components, including minerals, rocks, vegetation and soil. This paper ...
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Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction
... Figure 2: Potential applications of Deep Learning in fluorescence microscopy and key concepts. (a) Learning to reduce scattered light ’haze’ in light-sheet microscopy. (b) Learning spectral unmixing of ...
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A Review of Unsupervised Spectral Target Analysis for Hyperspectral Imagery
... finding spectral targets for ...linear spectral unmixing are considered where custom-designed synthetic images and real image scenes are used to conduct ...
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The effect of the point spread function on sub pixel mapping
... in the pixel i.e., spectral unmixing predictions, and Lk Vij is the coarse proportion estimated as convolution.. of the current SPM realization.[r] ...
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Application of Spectral Analysis in Mapping Hydrothermal Alteration of the Northwestern Part of the Kerman Cenozoic Magmatic Arc, Iran
... using spectral angle mapper (SAM) results in more accurate maps of alteration than those obtained using ...linear spectral unmixing (LSU) method, which produced a more accurate classification than ...
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Online Full Text
... Abstract— Spectral unmixing of hyperspectral images are based on the knowledge of a set of unknown endmembers. Unique characteristics of hyperspectral dataset enable different processing problems to be ...
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Mapping of Aluminous Rich Laterite Depositions through Hyper Spectral Remote Sensing
... dataset. Spectral subsetting of noise prone bands has been successfully ...filter. Spectral signatures of sam- ples were derived from the processed ...data. Spectral signature of each sample and ...
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Comparative infrared spectra analysis of one territory soil humic acids by IR-EXPERT computer system
... Figure 1 shows a comparison of the IR spectra of sample 4 and spectrum of compounds from the DB (No. reg =29041) with the best degree of overlap with the query spectrum (the coefficient of spectral similarity ...
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