Search results for "multispectral image"
showing 10 items of 192 documents
Quality enhancement of multispectral images for skin cancer optical diagnostics
2018
Melanoma is the least common but deadliest skin cancer, accounting for only about 1% of all cases, but is the cause of the vast majority of skin cancer death. In some parts of the world, especially among western countries, melanoma is becoming more common every year. The detection of melanoma in early stage can be helpful to cure it. Unfortunately, long ques and high prices for dermatology service can result in the skin cancer diagnosis at its later stage, thus increasing the risk of mortality for the patient. It is important to provide a non-invasive optical device for primary care physicians to help diagnose different skin malformation based on obtained optical images. Such device will be…
Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study
2017
Abstract Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and…
Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels
2016
The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derived from a set of images of benign nevi and melanomas with known diagnosis. Classification is done applying weighted majority rule to results of thresholding. Verification against the available multispectral images of 32 melanomas and 94 benign nevi has shown that the method using three spectral bands provided zero false negative and four false posi…
Real-time Multispectral Image Processing and Registration on 3D Point Cloud for Vineyard Analysis
2021
International audience; Nowadays, precision agriculture and precision viticulture are under strong development. In order to accomplish effective actions, robots require robust perception of the culture and the surrounding environment. Computer vision systems have to identify plant parts (branches, stems, leaves, flowers, fruits, vegetables, etc.) and their respective health status. Moreover, they must merge various plant information, to measure agronomic indices, to classify them and finally to extract data to enable the agriculturist or expert to make a relevant decision. We propose a real-time method to acquire, process and register multispectral images fused to 3D. The sensors system, co…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in situ air temperature observations
2012
Abstract The two-source energy balance (TSEB) model uses remotely sensed maps of land–surface temperature (LST) along with local air temperature estimates at a nominal blending height to model heat and water fluxes across a landscape, partitioned between dual sources of canopy and soil. For operational implementation of TSEB, however, it is often difficult to obtain representative air temperature data that are compatible with the LST retrievals, which may themselves have residual errors due to atmospheric and emissivity corrections. To address this issue, two different strategies in applying the TSEB model without requiring local air temperature data were tested over a typical Mediterranean…
Noncontact monitoring of vascular lesion phototherapy efficiency by RGB multispectral imaging.
2013
A prototype low-cost RGB imaging system consisting of a commercial RGB CMOS sensor, RGB light-emitting diode ring light illuminator, and a set of polarizers was designed and tested for mapping the skin erythema index, in order to monitor skin recovery after phototherapy of vascular lesions, such as hemangiomas and telangiectasias. The contrast of erythema index (CEI) was proposed as a parameter for quantitative characterization of vascular lesions. Skin recovery was characterized as a decrease of the CEI value relative to the value before the treatment. This approach was clinically validated by examining 31 vascular lesions before and after phototherapy.
Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
2009
Interest in remote sensing (RS) of solar-induced chlorophyll fluorescence (F) by terrestrial vegetation is motivated by the link of F to photosynthetic efficiency which could be exploited for large scale monitoring of plant status and functioning. Today, passive RS of F is feasible with different prototypes and commercial ground-based, airborne, and even spaceborne instruments under certain conditions. This interest is generating an increasing number of research projects linking F and RS, such as the development of new F remote retrieval techniques, the understanding of the link between the F signal and vegetation physiology and the feasibility of a satellite mission specifically designed f…
Challenges of automatic processing of large amount of skin lesion multispectral data
2020
This work will describe the challenges involved in setting up automatic processing for a large differentiated data set. In this study, a multispectral (skin diffuse reflection images using 526nm (green), 663nm (red), and 964nm (infrared) illumination and autofluorescence (AF) image using 405 nm excitation) data set with 756 lesions (3024 images) was processed. Previously, using MATLAB software, finding markers, correctly segmenting images with dark edges and image alignment were the main causes of the problems in automatic data processing. To improve automatic processing and eliminate the use of licensed software, the latter was substituted with the open source Python environment. For more …
Efficient Kernel Cook's Distance for Remote Sensing Anomalous Change Detection
2021
Detecting anomalous changes in remote sensing images is a challenging problem, where many approaches and techniques have been presented so far. We rely on the standard field of multivariate statistics of diagnostic measures, which are concerned about the characterization of distributions, detection of anomalies, extreme events, and changes. One useful tool to detect multivariate anomalies is the celebrated Cook's distance. Instead of assuming a linear relationship, we present a novel kernelized version of the Cook's distance to address anomalous change detection in remote sensing images. Due to the large computational burden involved in the direct kernelization, and the lack of out-…