Search results for "Multispectral"
showing 10 items of 242 documents
Identification of the most informative wavelengths for non-invasive melanoma diagnostics in spectral region from 450 to 950 nm
2020
In this study 300 skin lesion (including 32 skin melanomas) multispectral data cubes were analyzed. The multi-step and single step machine learning approaches were analyzed to find the wavebands that provide the most information that helps discriminate skin melanoma from other benign pigmented lesions. The multi-step machine learning approach assumed training several models but proved itself to be ineffective. The reason for that is a necessity to train a segmentation model on a very small dataset and utilization of standard machine learning classifier which have shown poor classification performance. The single-step approach is based on a deep learning neural network. We have conducted 260…
Semi-Supervised Classification Method for Hyperspectral Remote Sensing Images
2004
A new approach to the classification of hyperspectral images is proposed. The main problem with supervised methods is that the learning process heavily depends on the quality of the training data set. In remote sensing, the training set is useful only for simultaneous images or for images with the same classes taken under the same conditions; and, even worse, the training set is frequently not available. On the other hand, unsupervised methods are not sensitive to the number of labelled samples since they work on the whole image. Nevertheless, relationship between clusters and classes is not ensured. In this context, we propose a combined strategy of supervised and unsupervised learning met…
Dynamic best spectral bands selection for face recognition
2014
In this paper, face recognition in uncontrolled illumination conditions is investigated. A twofold contribution is proposed. First, three state-of-art algorithms, namely Multiblock Local Binary Pattern (MBLBP), Histogram of Gabor Phase Patterns (HGPP) and Local Gabor Binary Pattern Histogram Sequence (LGBPHS) are evaluated upon the IRIS-M3 face database to study their robustness against a high illumination variation conditions. Second, we propose to use visible multispectral images, provided by the same face database, to enhance the performance of the three mentioned algorithms. To reduce the high data dimensionality introduced by the use of multispectral images, we have designed a system t…
Validation of temperature-emissivity separation and split-window methods from TIMS data and ground measurements
2003
Abstract Land surface temperature retrieved with temperature-emissivity separation (TES) and split-window (SW) algorithms from six-channel Thermal Infrared Multispectral Scanner (TIMS) data in the HAPEX-Sahel experiment agreed with contemporaneous ground temperature measurements to within ±1 °C (TES and SW with channels at 10.8 and 11.7 μm, or SW-56). The SW algorithm used with TIMS channels at 8.4 and 8.7 μm (SW-12) underestimated ground temperatures by 2–5 °C. The TES method required atmospheric correction of at-sensor radiances, which was done with local radiosonde data and MODTRAN 4, and an empirical relationship between the spectral range of emissivity and its minimum value. Emissivity…
Color and multispectral image processing for the detection of inflammatory lesions of the stomach
2019
The work presented in this manuscript is part of the ANR project EMMIE. This project aims to develop an innovative multimodal system for the detection of inflammatory lesions in the stomach. To this purpose, a prototype has been developed to be able to acquire NBI endoscopic images and multispectral images during human's antrum exploration. The prototype is made of a standard endoscope and multispectral images.The prototype can acquire two types of data: NBI images and spectra. These two modalities are processed independently. Common image processing features are used to recognize four kind of diseases: active gastritis, chronic gastritis, metaplasia and atrophy. In addition, visual based f…
Genetic colour variation visible for predators and conspecifics is concealed from humans in a polymorphic moth
2022
The definition of colour polymorphism is intuitive: genetic variants express discretely coloured phenotypes. This classification is, however, elusive as humans form subjective categories or ignore differences that cannot be seen by human eyes. We demonstrate an example of a 'cryptic morph' in a polymorphic wood tiger moth (Arctia plantaginis), a phenomenon that may be common among well-studied species. We used pedigree data from nearly 20,000 individuals to infer the inheritance of hindwing colouration. The evidence supports a single Mendelian locus with two alleles in males: WW and Wy produce the white and yy the yellow hindwing colour. The inheritance could not be resolved in females as t…
Convolutional Neural Networks for Multispectral Image Cloud Masking
2020
Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.
Improved Temperature and Emissivity Separation Algorithm for Multispectral and Hyperspectral Sensors
2017
The Temperature and Emissivity Separation (TES) algorithm was originally developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). This paper focuses on improving the TES algorithm. The main modification is the replacement of the normalized emissivity module with a new module, which is based on the smoothing of spectral radiance signatures. Smoothing is performed by estimating emissivity using an optimized approximation of the relationship between brightness temperature and emissivity. The improved TES algorithm, which is called Optimized Smoothing for Temperature Emissivity Separation (OSTES), was first tested on simulated data from three different sensors, …
Smartphone snapshot mapping of skin chromophores under triple-wavelength laser illumination
2017
Abstract Chromophore distribution maps are useful tools for skin malformation severity assessment and for monitoring of skin recovery after burns, surgeries, and other interactions. The chromophore maps can be obtained by processing several spectral images of skin, e.g., captured by hyperspectral or multispectral cameras during seconds or even minutes. To avoid motion artifacts and simplify the procedure, a single-snapshot technique for mapping melanin, oxyhemoglobin, and deoxyhemoglobin of in-vivo skin by a smartphone under simultaneous three-wavelength (448–532–659 nm) laser illumination is proposed and examined. Three monochromatic spectral images related to the illumination wavelengths …
Imaging of laser-excited tissue autofluorescence bleaching rates.
2009
Experimental methodology for imaging of laser-excited tissue autofluorescence bleaching rates has been developed and clinically tested. The fluorescence images were periodically captured from the same tissue area over a certain time, with subsequent detection of the fluorescence intensity decrease rate at each image pixel and further imaging the planar distribution of those values. Spectral features at each image pixel were analyzed with a hyperspectral imaging camera. Details of the equipment and image processing are described as well as some measurement results that confirm the feasibility of the proposed technology.