Results 111 to 120 of about 4,872 (167)

Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline. [PDF]

Remote Sens Environ, 2019
Zarco-Tejada PJ, Hornero A, Beck PSA, Kattenborn T, Kempeneers P, Hernández-Clemente R.   +5 more
europepmc   +1 more source

An Oil Slick Detection Method Based on Advanced Spectral DNA Encoding Strategy by Chinese Zhuhai-1 Satellite Imagery. [PDF]

Sensors (Basel)
Zhao D, Bi L, Feng J, Gao G, Qu C.
europepmc   +1 more source

Estimating high-resolution albedo for urban applications. [PDF]

Nat Commun
Fork D, Wesley EJ, Banerjee S, Batchu V, Chennapragada A, Crossan K, Cronkite-Ratcliff B, Delich E, Goulden T, Kansal M, Kemp J, Mackres E, Mayer Y, Milman R, Platt JC, Prabhakara S, Prasad G, Shetty S, Stanton C, Sun W, Hutyra LR.   +20 more
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Spatial-spectral resolution analysis using drone hyperspectral and satellite multispectral imagery for shallow coastal water monitoring. [PDF]

Sci Rep
Mederos-Barrera A, Eugenio F, Marcello J.   +2 more
europepmc   +1 more source

Remote Sensing Applications in Medicinal Plant Monitoring and Quality Assessment: A Review. [PDF]

Sensors (Basel)
Wang Z, Ji J, Chen G, Fan Y, Wang J, Yang Y, Wang X.   +6 more
europepmc   +1 more source

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Compression of hyperspectral imagery

Data Compression Conference, 2003. Proceedings. DCC 2003, 2003
High dimensional source vectors, such as those that occur in hyperspectral imagery, are partitioned into a number of subvectors of different length and then each subvector is vector quantized (VQ) individually with an appropriate codebook. A locally adaptive partitioning algorithm is introduced that performs comparably in this application to a more ...
Giovanni Motta, Francesco Rizzo, James A. Storer   +2 more
openaire   +1 more source

Band Sampling for Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2022
Band sampling (BSam) is an innovative concept for hyperspectral imaging, which is derived from signal sampling in communications/signal processing as well as sampling theory in information theory. It is quite different from band selection (BSel) in several aspects.
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Compressed hyperspectral imagery for forestry

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
Various compression schemes have been suggested for storage and distribution of hyperspectral remotely sensed data. Hyperspectral forestry applications that rely on the measurement of subtle variations in the spectral signature of the forest canopy can be affected by modification of the spectra induced by compression.
Andrew Dyk, David G. Goodenough, Suzanne Thompson, Christian Nadeau, Allan Hollinger, Shen-En Qian   +5 more
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Modeling and detection in hyperspectral imagery

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002
One aim of using hyperspectral imaging sensors is in discriminating man-made objects from dominant clutter environments. Sensors like Aviris or Hydice simultaneously collect hundreds of contiguous and narrowly spaced spectral band images for the same scene. The challenge lies in processing the corresponding large volume of data that is collected by the
Susan M. Schweizer, José M. F. Moura
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Interest segmentation of hyperspectral imagery

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010
In recent years, many new methods for analyzing spectral imagery have been introduced. These new methods have been developed to improve the analysis of hyperspectral imagery. Many of these techniques are data driven anomaly/target detection and spectral clustering algorithms which are used to decide whether a particular pixel or area is “interesting ...
Ariel Schlamm, David W. Messinger, William Basener   +2 more
openaire   +1 more source