Search results for "Multispectral"
showing 10 items of 242 documents
Multimodal device for assessment of skin malformations
2013
A variety of multi-spectral imaging devices is commercially available and used for skin diagnostics and monitoring; however, an alternative cost-efficient device can provide an advanced spectral analysis of skin. A compact multimodal device for diagnosis of pigmented skin lesions was developed and tested. A polarized LED light source illuminates the skin surface at four different wavelengths – blue (450 nm), green (545 nm), red (660 nm) and infrared (940 nm). Spectra of reflected light from the 25 mm wide skin spot are imaged by a CMOS sensor. Four spectral images are obtained for mapping of the main skin chromophores. The specific chromophore distribution differences between different skin…
Simulation of citrus orchard reflectance by means of a geometrical canopy model
1994
Computer simulation of the reflectance for citrus crops, by using a geometrical canopy model, has been carried out to analyse and interpret the reflectance values from Landsat-5 Thematic Mapper (TM...
Mapping Actual Evapotranspiration by Combining Landsat TM and NOAA-AVHRR Images: Application to the Barrax Area, Albacete, Spain
1998
Abstract A method that permits determination of actual evapotranspiration, ET, in heterogeneous areas has been proposed. It is based on the relation ET = ET m − B ( T s − T sm ), which combines meteorological, National Oceanic and Atmospheric Administration advanced very high resolution radiometer (NOAA-AVHRR), and Landsat thematic mapper (TM) data. Thus, the maximum evapotranspiration for each crop, ETm, is obtained from in situ measurements carried out in a meteorological station; the temperature difference between each pixel and the pixel that has the maximum evapotranspiration, Ts−Tsm, is calculated for each crop from NOAA-AVHRR data; and the crop distribution in the area is known throu…
Multi-spectral imaging analysis of pigmented and vascular skin lesions: results of a clinical trial
2011
A clinical trial comprising 266 pigmented lesions and 49 vascular lesions has been performed in three Riga clinics by means of multi-spectral imaging analysis. The imaging system Nuance 2.4 (CRI) and self-developed software for mapping of the main skin chromophores were used. The obtained results confirm clinical potential of this technology for non-contact quantitative assessment of skin pathologies.
Comparison of metrics to remove the influence of geometrical conditions on soil reflectance
2007
The objective of this work is to find the best metric to ignore the variations of soil reflectance induced by the solar-view angles geometry. Differences between spectra measured for the same soil under different observation and illumination configurations can leads to misclassifications. Using ninety two soils of different composition measured under twenty eight solar- view angles geometries, we tested 3 metrics : RMSE, SAM, R2 (the coefficient of determination) and we compared their performances. The best metric seems to be the coefficient of determination with 93 % of good classifications.
Learning spatial filters for multispectral image segmentation.
2010
International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.
Extension of luminance component based demosaicking algorithm to 4- and 5-band multispectral images
2021
Abstract Multispectral imaging systems are currently expanding with a variety of multispectral demosaicking algorithms. But these algorithms have limitations due to the remarkable presence of artifacts in the reconstructed image. In this paper, we propose a powerful multispectral image demosaicking method that focuses on the G band and luminance component. We've first identified a relevant 4-and 5-band multispectral filter array (MSFA) with the dominant G band and then proposed an algorithm that consistently estimates the missing G values and other missing components using a convolution operator and a weighted bilinear interpolation algorithm based on the luminance component. Using the cons…
Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging
2017
Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…
Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue
2008
In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.
Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval
2013
Abstract ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we f…