Estimating the number of endmembers in hyperspectral images using the normal compositional model and a hierarchical Bayesian algorithm. [PDF]
, 2010 This paper studies a semi-supervised Bayesian unmixing algorithm for hyperspectral images. This algorithm is based on the normal compositional model recently introduced by Eismann and Stein.
Eches, Olivier +2 more
core +1 more source
Remote Sensing, 2023 Neural network models for hyperspectral images classification are complex and therefore difficult to deploy directly onto mobile platforms. Neural network model compression methods can effectively optimize the storage space and inference time of the ...
Yu Lei +5 more
doaj +1 more source
Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery [PDF]
, 2009 This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Moussaoui, Saïd +10 more
core +1 more source
Hyperspectral image compression : adapting SPIHT and EZW to Anisotropic 3-D Wavelet Coding [PDF]
, 2008 Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity.
Christophe, Emmanuel +2 more
core +1 more source
Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model [PDF]
, 2012 This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian
Altmann, Yoann +3 more
core +1 more source
In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum
Journal of Biomedical Photonics & Engineering, 2018 The paper presents analysis of hyperspectral images for human skin cancer pathologies diagnostics. Hyperspectral images data contained backscattered spectra of normal skin and tumors. Analysis of hyperspectral images provided information about hemoglobin
Ivan A. Bratchenko +10 more
doaj +1 more source
Target Detection System Design for Domestic Areas in Iran: Case Study in Abadan and Ahvaz, Using Satellite Multi-spectral Images of Landsat 8 and Sentinel 2 [PDF]
فناوری در مهندسی هوافضا, 2020 Hyperspectral images provide worthful spectral information for target detection. Since these images are not available in Iran, we use multi-spectral images with approximately 10 bands.
Maryam Imani
doaj
TRANSFER LEARNING WITH LIMITED SAMPLES FOR THE SAME SOURCE HYPERSPECTRAL REMOTE SENSING IMAGES CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 A classification method for hyperspectral datasets with a limited number of samples based on transferred convolutional neural network (CNN) is proposed. For the CNN model, a lot of labeled samples are needed for the classification of hyperspectral images,
W. Li, Q. Liu, Y. Wang, H. Li
doaj +1 more source
MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES
Image Analysis & Stereology, 2011 The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume +2 more
openaire +7 more sources
Smart Agricultural TechnologyThe accurate and effective monitoring of rice nitrogen status using hyperspectral datasets and estimation models is important for precision agriculture and intelligent breeding.
Zhonglin Wang +11 more
doaj +1 more source