Search results for "Spectral imaging"
showing 10 items of 311 documents
Evaluation of Erythema Severity in Dermatoscopic Images of Canine Skin: Erythema Index Assessment and Image Sampling Reliability.
2021
The regular monitoring of erythema, one of the most important skin lesions in atopic (allergic) dogs, is essential for successful anti-allergic therapy. The smartphone-based dermatoscopy enables a convenient way to acquire quality images of erythematous skin. However, the image sampling to evaluate erythema severity is still done manually, introducing result variability. In this study, we investigated the correlation between the most popular erythema indices (EIs) and dermatologists’ erythema perception, and we measured intra- and inter-rater variability of the currently-used manual image-sampling methods (ISMs). We showed that the EIBRG, based on all three RGB (red, green, and blue) channe…
Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network
2020
In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator tries to produce data that is similar to the measured data, and the discriminator tries to correctly classify the data as fake or real. This is a reinforcement learning model, where both models get reinforcement based on their performance. In the training of the discriminator we use data measured from skin cancer patients. The aim for the study is to develop a generator for augmenting hyperspectral skin cancer imagery. peerReviewed
CEFLES2: The remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the …
2009
The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO<sub>2</sub> fluxes. It was combined with extensive ground-based quantification of leaf- and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype ai…
Impact of spatial resolution and satellite overpass time on evaluation of the surface urban heat island effects
2012
Abstract Surface Urban Heat Island (SUHI) effect is defined as the increased surface temperature in urban areas in contrast to surrounding cooler temperatures in rural areas. In this paper, we study the characteristics that a spaceborne sensor must satisfy in terms of spatial resolution and overpass time to properly monitor the SUHI effect. For this, Land Surface Temperature (LST) maps, generated at different spatial resolution using the Airborne Hyperspectral Scanner (AHS) imagery, and in situ data of air temperature and LST obtained from the framework of the Dual-use European Security IR Experiment 2008 have been considered for the city of Madrid (Spain). The results showed that (1) spati…
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…
Hyperspectral venous image quality assessment for optimum illumination range selection based on skin tone characteristics
2014
Background Subcutaneous veins localization is usually performed manually by medical staff to find suitable vein to insert catheter for medication delivery or blood sample function. The rule of thumb is to find large and straight enough vein for the medication to flow inside of the selected blood vessel without any obstruction. The problem of peripheral difficult venous access arises when patient’s veins are not visible due to any reason like dark skin tone, presence of hair, high body fat or dehydrated condition, etc. Methods To enhance the visibility of veins, near infrared imaging systems is used to assist medical staff in veins localization process. Optimum illumination is crucial to obt…
Lossless coding of hyperspectral images with principal polynomial analysis
2014
The transform in image coding aims to remove redundancy among data coefficients so that they can be independently coded, and to capture most of the image information in few coefficients. While the second goal ensures that discarding coefficients will not lead to large errors, the first goal ensures that simple (point-wise) coding schemes can be applied to the retained coefficients with optimal results. Principal Component Analysis (PCA) provides the best independence and data compaction for Gaussian sources. Yet, non-linear generalizations of PCA may provide better performance for more realistic non-Gaussian sources. Principal Polynomial Analysis (PPA) generalizes PCA by removing the non-li…
Software Framework for Hyperspectral Data Exploration and Processing in MATLAB
2017
This paper presents a user introduction and a general overview of the MATLAB software package hsicube developed by the author for simplifying the data manipulation and visualization tasks often encountered in hyperspectral analysis work, and the design principles and software development methods used by the author. The framework implements methods for slicing, masking, visualization and application of existing functions to hyperspectral data cubes without the need to use explicit indexing or reshaping, as well as enabling expressive syntax for combining these operations on the command line for highly efficient data analysis workflows. It also includes utilities for interfacing with existing…
In-scene atmospheric correction of hyperspectral thermal infrared images with nadir, horizontal, and oblique view angles
2012
Atmospheric corrections for hyperspectral thermal images acquired with nadir, horizontal, and oblique views have typically relied on atmospheric modelling software, such as Moderate Resolution Atmospheric Transmission MODTRAN, to estimate atmospheric parameters. Data-only corrections, which require only information from the scene, are more versatile and less labour intensive, but do not yet seem to have been applied to horizontal and oblique views. Here, we apply, and modify where necessary, one published data-only algorithm in-scene atmospheric correction ISAC to nadir, horizontal, and slanted views The Aerospace Corporation's Spatially Enhanced Broadband Array Spectrograph System SEBASS a…
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…