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July 2012 - present
January 1981 - March 2016
Publications
Publications (126)
Ultrasonic non-destructive testing (UT) is a proficient method for detecting damage in composite materials; however, conventional manual testing procedures are time-consuming and labor-intensive. We propose a semi-automated defect segmentation methodology employing a convolutional neural network (CNN) on 3D ultrasonic data, facilitated by the fusio...
Medical image fusion has many applications to healthcare that is accomplished by extracting and then combining the complementary information from multiple medical images into a single image. The pulse coupled neural network (PCNN) is greatly applied to image fusion due to its efficient coupling of surrounding neurons, but suffers from network compl...
Spatiotemporal fusion (STF) methods are a paramount solution for generating high spatial and temporal time series, overcoming the limitations of spatial and temporal resolution of satellite data. STF methods typically rely on band-by-band fusion, assuming spectral similarities. However, selecting the optimal band for fusion becomes challenging when...
Crop yield forecasting allows farmers to make decisions in advance to improve farm management and logistics during and after harvest. In this sense, crop yield potential maps are an asset for farmers making decisions about farm management and planning. Although scientific efforts have been made to determine crop yields from in situ information and...
Landslide inventories are crucial to studying the dynamics, associated risks, and effects of these geomorphological processes on the evolution of mountainous landscapes. The production of landslide maps is mainly based on manual visual interpretation methods of aerial and satellite images combined with field surveys. In recent times, advances in ma...
Fast and accurate diagnosis is essential for the triage and management of pneumonia, particularly in the current scenario of a COVID-19 epidemic outbreak, where this pathology is a major symptom. With the objective of providing tools for that purpose, this work assesses the potential of three textural image characterisation methods: radiomics, frac...
The continuous growth of the world’s population requires immediate action to ensure food security. Sorghum is among the five most-produced cereals and is a dietary staple in many developing countries. Therefore, it is of great importance to obtain precise information for improving cereal productivity. An indicator for estimating sorghum yields is t...
In this work, we present a new methodology integrating data from multiple sources, such as observations from the Landsat-8 (L8) and Sentinel-2 (S2) satellites, with information gathered in field campaigns and information derived from different public databases, in order to characterize the water demand of crops (potential and estimated) in a spatia...
Coastal areas are key to sustaining biodiversity, but their complexity and variability makes their analysis challenging. On the other hand, mountain ecosystems include a large percentage of the global biodiversity and their monitoring is essential, as they are especially vulnerable to climate change. In this context, remote sensing offers a cost-ef...
Xylem is a vascular tissue that conducts sap (water and dissolved minerals) from the roots to the rest of the plant while providing physical support and resources. Sap is conducted within dead hollow cells (called vessels in flowering plants) arranged to form long pipes. Once formed, vessels do not change their structure and last from years to mill...
In the scenario of current water scarcity caused by climate change and increasing water demand for food production, farmers must adapt their water management practices by shifting from supply-driven water management to demand-driven water management, considering trade-offs among quality, quantity and costs. Thus, agricultural practices must take fu...
The applications of object-based image analysis (OBIA) in remote sensing studies have received a considerable amount of attention over the recent decade due to dramatically increasing of the spatial resolution of satellite imaging sensors for earth observation. In this study, an unsupervised methodology based on OBIA paradigm for the estimation of...
In clustering, similarity measure has been one of the major factors for discovering the natural grouping of a given dataset by identifying hidden patterns. To determine a suitable similarity measure is an open problem in clustering analysis for several years. The purpose of this study is to make known a divergence based similarity measure. The noti...
Accurate and up-to-date information on the spatial and geographical characteristics of agricultural areas is an indispensable value for the various activities related to agriculture and research. Most agricultural studies and policies are carried out at the field level, for which precise boundaries are required. Today, high-resolution remote sensin...
During the last decades, ecosystems have suffered a decline in natural resources due to climate change and anthropogenic pressure. Specifically, the European rabbit introduced by humans, as well as drought episodes, have led to a change in the vegetation structure of a mountainous ecosystem: Teide National Park in Spain. Teide managers studied, wit...
The use of cutting-edge geospatial technologies to monitor ecosystems and the development of tailored tools for assessing such natural areas is a fundamental task. In this context, the growing availability of hyperspectral (HS) imagery from satellite and aerial platforms can provide valuable information for the sustainable management of ecosystems....
Alzheimer's disease (AD) is characterized by a progressive deterioration of cognitive and behavioral functions as a result of the atrophy of specific regions of the brain. It is estimated that by 2050 there will be 131.5 million people affected. Thus, there is an urgent need to find biological markers for its early detection and monitoring. In this...
The widespread adoption of Electronic Health Records (EHRs) is generating an ever-increasing amount of unstructured clinical texts. Processing time expressions from these domain-specific-texts is crucial for the discovery of patterns that can help in the detection of medical events and building the patient’s natural history. In medical domain, the...
Climate change and anthropogenic pressure are causing an indisputable decline in biodiversity; therefore, the need of environmental knowledge is important to develop the appropriate management plans. In this context, remote sensing and, specifically, hyperspectral imagery (HSI) can contribute to the generation of vegetation maps for ecosystem monit...
A considerable amount of research has been done since long to select an appropriate similarity or dissimilarity measure in cluster analysis for exposing the natural grouping in an input dataset. Still, it is an open problem. In recent years, the research community is focusing on divergence-based non-Euclidean similarity measure in partitional clust...
The outlining of agricultural land is an important task for obtaining primary information used to create agricultural policies, estimate subsidies and agricultural insurance, and update agricultural geographical databases, among others. Most of the automatic and semi-automatic methods used for outlining agricultural plots using remotely sensed imag...
Image fusion (pan-sharpening) plays an important role in remote sensing applications. Mainly, this process allows to obtain images of high spatial and spectral resolution. However, pan-sharpened images usually present spectral and spatial distortion when comparing with the source images. Because of this, the evaluation of the spectral quality of pa...
One field of application of Big Data and Artificial Intelligence that is receiving increasing attention is the biomedical domain. The huge volume of data that is customary generated by hospitals and pharmaceutical companies all over the world could potentially enable a plethora of new applications. Yet, due to the complexity of such data, this come...
If Electronic Health Records contain a large amount of information about the patient’s condition and response to treatment, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its extraction and analysis. We here report on a first integration of an NLP framework for the analysis...
Alzheimer’s disease (AD) represents the prevalent type of dementia in the elderly, and is characterized by the presence of neurofibrillary tangles and amyloid plaques that eventually leads to the loss of neurons, resulting in atrophy in specific brain areas. Although the process of degeneration can be visualized through various modalities of medica...
Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform. TIR resolution is often not suitable for monitoring crop conditions of fragmented farming lands, e.g., the accurate estimates of evapotranspiration (ET) based on surface energy balance from remote sensing fo...
Earth Observation (EO) can be defined as the gathering of information about Earth’s physical, chemical and biological systems using remote sensing technologies such as satellites and aerial sensors, supplemented (Science Communication Unit, 2013) by ground-based observations and other surveying techniques. EO is used to monitor and assess the statu...
In the last decades, there has been a decline in ecosystems natural resources. The objective of the study is to develop advanced image processing techniques applied to high resolution remote sensing imagery for the ecosystem conservation. The study area is focused in three ecosystems from The Canary Islands, Teide National Park, Maspalomas Natural...
Hyperspectral imagery (HSI) integratesmany continuous and narrowbands that cover different regions of the electromagnetic spectrum. However, the main challenge is the high dimensionality of HSI data due to the 'Hughes' phenomenon. Thus, dimensionality reduction is necessary before applying classification algorithms to obtain accurate thematic maps....
The Fractal Dimension (FD) of an image defines the roughness using a real number which is highly associated with the human perception of surface roughness. It has been applied successfully for many computer vision applications such as texture analysis, segmentation and classification. Several techniques can be found in literature to estimate FD. On...
Somniloquy is a parasomnia that refers to talking aloud while sleep. This parasomnia usually happens during transitory arousals from NREM sleep. The recording of these parasomnias could be useful to help in the diagnosis of certain psychological pathologies given that they can reflect a state of anxiety or some behaviors which could be identified a...
In recent decades, there has been a decline in ecosystem services. Thus, the development of reliable methodologies to monitor ecosystems is becoming important. In this context, the availability of very high resolution sensors offer practical and cost-effective means for good environmental management. However, improvements in the data received are b...
Efficient water management in agriculture requires an accurate estimation of evapotranspiration (ET). Even though local measurements can be used to estimate the components of the surface energy balance, these values cannot be extrapolated to large areas due to the heterogeneity and complexity of agricultural and natural land surfaces and the dynami...
Determining the severity and potential aggressiveness of breast cancer is an important step in the determination of the treatment options for a patient. Mitosis activity is one of the main components in breast cancer severity grading. Currently, mitosis counting is a laborious, prone to processing errors, done manually by a pathologist. This paper...
Satellite sensors usually provide two types of data: panchromatic and multispectral images which are characterized by their high spatial resolution and high spectral resolution respectively. In this context, the fusion techniques or pansharpening consist of merging these different aspects to obtain a fused (or pan-sharpened) image with high spatial...
A correct delineation of agricultural parcels is a primary requirement for any parcel-based application such as the estimate of agricultural subsidies. Currently, high-resolution remote-sensing images provide useful spatial information to delineate parcels; however, their manual processing is highly time consuming. Thus, it is necessary to create m...
Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources’ reduction is conce...
Water resources are the main productive source in Chile. Growing competition for water use causes conflicts which end up in courts (Courts of Appeal and The Supreme Court). Legal disputes end when the courts issue a judgement which is recorded. The volume of court decisions made makes the task of searching, analyzing, and extracting knowledge from...
Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical narratives (unstructured data) making it possible to perform context-based searches. Current approaches to process the unstructured texts in EHRs are based in applying text mining or natural language...
The generalized adoption of Electronic Medical Records (EMR) together with the need to give the patient the appropriate treatment at the appropriate moment at the appropriate cost is demanding solutions to analyze the information on the EMR automatically. However most of the information on the EMR is non-structured: texts and images. Extracting kno...
Remote sensing (RS) has played an important role in extensive agricultural monitoring and management for several decades. However, the current spatial resolution of satellite imagery does not have enough definition to generalize its use in highly-fragmented agricultural landscapes, which represents a significant percentage of the world's total cult...
A new image fusion algorithm based on the visible and thermal images for face recognition is presented in this paper. The new fusion algorithm derives the benefit from both the modalities images. The proposed fusion process is the weighted sum of thermal and visible face information with two weighting factors (Formula presented.) and (Formula prese...
Recently deep learning-based methods have demonstrated excellent performance on different artificial-intelligence tasks. Even though, in the last years, several related works are found in the literature in the remote sensing field, a small percentage of them address the classification problem. These works propose schemes based on image patches to p...
Water demand and climate variability increases competition and tension between water users–agricultural, industrial, mining, hydropower–and local communities. Since 1981, the Water Code has regulated water allocation through private individual property rights, fostering markets as the distribution mechanism among users. When legal conflicts occur b...
The new generation of artificial satellites is providing a huge amount of Earth observation images whose exploitation can report invaluable benefits, both economical and environmental. However, only a small fraction of this data volume has been analyzed, mainly due to the large human resources needed for that task. In this sense, the development of...
Resumen: En este trabajo se describe una metodología para la evaluación de la calidad espacial de imágenes fusionadas de teledetección. A pesar de que existen numerosos indicadores de ca lidad publicados en la literatura científica, no existe un consenso sobre su rendimiento. En general utilizan el píxel como elemento de referen cia para el cálcu l...
Resumen: La fusión de imágenes juega un papel importante en las aplicaciones de teledetección en las que se necesita un análisis visual. Debido a esto, la evaluación de la calidad espectral de las imágenes fusionadas es un tema fundamental para optimizar y comparar el resultado de distintos algoritmos. El objetivo de este trabajo es explorar el uso...
Resumen: La delimitación de parcelas agrícolas a gran escala juega un papel primordial en los estudios relacionados con el manejo y la gestión de las explotaciones agrícolas. Por ello, es necesario el diseño de métodos computacionales que realicen esta labor de forma automática, rápida y precisa. El objetivo de este trabajo es proporcionar un marco...
This paper presents an algorithm for feature selection based on particle swarm optimization (PSO) for thermal face recognition. The total algorithm goes through many steps. In the very first step, thermal human face image is preprocessed and cropping of the facial region from the entire image is done. In the next step, scale invariant feature trans...
A correct assessment of pan-sharpened remote sensing imagery (fusion of panchromatic and multispectral images) enables the improvement and ranking of pan sharpening algorithms. For this purpose, numerous quality indicators have been published in the literature; however, there is no consensus on their performance. In general, the pixel is used as a...
The identification of vegetation using remote sensing imagery is an important area of work with numerous applications such as the analysis of deforestation and crop monitoring. This work focuses on locating populations of an endemic shrub of the Canary Islands that grows in Teide National Park: the Teide broom. The objective is to determine automat...
Over recent decades, remote sensing has emerged as an effective tool for improving agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hier...
Very high resolution remotely sensed images are an important tool for monitoring fragmented agricultural landscapes, which allows farmers and policy makers to make better decisions regarding management practices. An object-based methodology is proposed for automatic generation of thematic maps of the available classes in the scene, which combines e...
The adoption of hospital EHR technology is significantly growing and expected to grow. Digitalized information is the basis for health analytics. In particular, patient medical records contain valuable clinical information written in narrative form that can only be extracted after it has been previously preprocessed with Natural Language Processing...
Despite of the spread of Electronic Health Records (EHRs) in Spanish hospitals and Spanish occupying the second place in the ranking of number of speakers, to the best of our knowledge there are no natural language processing tools for medical texts written in Spanish.
This paper presents an approach based on OpenNLP to process natural language tex...
This paper presents a robust approach for recognition of thermal face images based on decision level fusion of 34 different region classifiers. The region classifiers concentrate on local variations. They use singular value decomposition (SVD) for feature extraction. Fusion of decisions of the region classifier is done by using majority voting tech...
A robust thermal face recognition method has been discussed in this work. A new feature extraction technique named as Histogram of Bunched Intensity Values (HBIVs) is proposed. A heterogeneous classifier ensemble is also presented here. This classifier consists of three different classifiers namely, a five layer feed-forward backpropagation neural...
Even though images with high and very high spatial resolution exhibit higher levels of detailed features, traditional image processing algorithms based on single pixel analysis are often not capable of extracting all their information. To solve this limitation, object-based image analysis approaches (OBIA) have been proposed in recent years.
One of...
This work implements an object-oriented multispectral image classification to quantify turbidity levels in the Grande Lagoon of San Pedro (Chile) (36° 51' S, 73° 06' W). The first step in this methodology is multiscale segmentation; then, to characterize the lagoon cover, different classes are defined according to the selection of training areas as...
This work implements an object-oriented multispectral image classification to quantify turbidity levels in the Grande Lagoon of San Pedro (Chile) (36° 51' S, 73° 06' W). The first step in this methodology is multiscale segmentation; then, to characterize the lagoon cover, different classes are defined according to the selection of training areas as...
This paper presents a new methodology, simple and affordable, for the definition and characterization of objects at different scales in high spatial resolution images. The objects have been generated by integrating texturally and spectrally homogeneous segments. The former have been obtained from the segmentation of Wavelet coefficients of the panc...
The Self-Organizing Map (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption ab...
Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e. artifacts, in the resulting fused images. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values ass...
The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantag...
RESUMEN En este trabajo se presenta una nueva metodología para la detección de cambios multi-escala en imágenes de satélite, basada en criterios orientados a objetos. En esta estrategia se aplican la dimensión fractal y las características espectrales de las imágenes como línea de base de análisis. De esta forma es posible detectar cambios morfológ...
Remote sensing can be defined as the technique that facilitates the acquisition of land surface data without contact with the material object of observation. The development of tools for analyzing and processing multispectral images captured by sensors aboard satellites has provided the automation of tasks that could not be possible otherwise. The...
Two new simplified algorithms for Fuzzy ART have been developed. Onlycommitted category nodes C rather than the full capacity of the category nodes N (N>>C) are involved in the determination of the winning categoy node. In addition tothat, the initialization for weights and choice values has been eliminated.This reduces a lot the training time with...
Self-organizing map (SOM) is a neural network model widely used in high dimensional data visualization processes. A trained
SOM provides a simplified data model as well as a projection of the multidimensional input data into a bi-dimensional plane
that reflects the relationships involving the training patters. Visualization methods based in SOM exp...
The fusion image strategies are a good solution to obtain a synthetic image with high spatial and spectral characteristics simultaneously. Some of them are based on the Wavelet Transform, computed by means of the à trous algorithm (AWT). Most of them do not differentiated between spectral bands. In this sense, a new approach that weights differentl...
Currently, there exist many research areas that produce large multivariable datasets that are difficult to visualize in order to extract useful information. Kohonen self organizing maps have been used successfully in the visualization and analysis of multidimensional data. In this work, a projection technique that compresses multidimensional datase...
This paper proposes a new fusion method for multiespectral (MULTI) and panchromatic (PAN) images that uses a highly anisotropic and redundant representation of images. This methodology join the simplicity of the Wavelet transform, calculated using the à trous algorithm, with the benefits of multidirectional transforms like Contourlet Transform. Tha...
This paper proposes a method to determine, in an objective and accurate way, the weighting factor (a) to be applied to the detailed panchromatic image information that will be integrated with the background multispectral image information to obtain the "best" fused image with the same spatial and spectral quality. The fusion method is a weighting v...
It is proposed to improve the precision estimation of the representative characteristics of the quality characteristics of waters of a lake through the use of fused images. For that, images captured by the sensors of the Landsat 7 satellite have been used. The fused images have been obtained by means of a new fusion methodology, conceptually inspir...
It is proposed to improve the precision estimation of the representative characteristics of the quality characteristics of waters of a lake through the use of fused images. For that, images captured by the sensors of the Landsat 7 satellite have been used. The fused images have been obtained by means of a new fusion methodology, conceptually inspir...
Se propone mejorar la precisión en la estimación de características representativas de la calidad de las aguas de un lago mediante el uso de imágenes de satélite fusionadas. Las imágenes satelitales fuente han sido capturadas por los sensores a bordo del satélite Landsat 7. Las imágenes fusionadas se han obtenido mediante una nueva metodología de f...
techniques to perform remote sensed image fusion are based on multiresolution analysis. This kind of images analysis requires the decomposition of the image at differente scales or levels, depending the fusion results on this level. Then, the two main objectives of this work are: to investigate the influence of the source images spatial characteris...
