Prof. Francisco Javier Marcello-Ruiz Profile

Prof. Francisco Javier Marcello-Ruiz

Associate Professor at Univ de Las Palmas de Gran Canaria

SPIE Involvement:

Author

Publications (12)

Proceedings Article | 31 January 2020 Paper

Comparative study of upsampling methods for super-resolution in remote sensing

Luis Salgueiro Romero, Javier Marcello, Verónica Vilaplana

Proceedings Volume 11433, 114331J (2020) https://doi.org/10.1117/12.2557357

KEYWORDS: RGB color model, Super resolution, Remote sensing, Image resolution, Spatial resolution, Earth observing sensors

Read Abstract +

Proceedings Article | 5 October 2017 Presentation + Paper

Vulnerable land ecosystems classification using spatial context and spectral indices

Edurne Ibarrola-Ulzurrun, Consuelo Gonzalo-Martín, Javier Marcello

Proceedings Volume 10428, 104280V (2017) https://doi.org/10.1117/12.2278496

KEYWORDS: Vegetation, Ecosystems, Image classification, Remote sensing, Image segmentation, Spatial resolution, Matrices, Data acquisition, Associative arrays, Environmental sensing

Read Abstract +

Proceedings Article | 4 October 2017 Presentation + Paper

Evaluation of dimensionality reduction techniques in hyperspectral imagery and their application for the classification of terrestrial ecosystems

Edurne Ibarrola-Ulzurrun, Javier Marcello-Ruiz, Consuelo Gonzalo-Martín

Proceedings Volume 10427, 104270G (2017) https://doi.org/10.1117/12.2278501

KEYWORDS: Hyperspectral imaging, Image classification, Principal component analysis, Independent component analysis, Ecosystems, Sensors, Spatial resolution, Detection and tracking algorithms, Remote sensing, Electromagnetism

Read Abstract +

Proceedings Article | 18 October 2016 Paper

Pansharpening in coastal ecosystems using Worldview-2 imagery

Edurne Ibarrola-Ulzurrun, Javier Marcello-Ruiz, Consuelo Gonzalo-Martin

Proceedings Volume 10004, 100041U (2016) https://doi.org/10.1117/12.2241506

KEYWORDS: Image fusion, Ecosystems, Image quality, Wavelets, Sensors, Visualization, Distortion, Visual analytics, Modulation transfer functions, Image processing

Read Abstract +

Proceedings Article | 18 October 2016 Presentation + Paper

Influence of pansharpening techniques in obtaining accurate vegetation thematic maps

Edurne Ibarrola-Ulzurrun, Consuelo Gonzalo-Martin, Javier Marcello-Ruiz

Proceedings Volume 10005, 1000515 (2016) https://doi.org/10.1117/12.2241501

KEYWORDS: Image fusion, Vegetation, Image classification, Ecosystems, Wavelets, Image segmentation, Roads, Image processing, Accuracy assessment, Mahalanobis distance

Read Abstract +

Proceedings Article | 8 November 2012 Paper

Color and spatial distortions of pan-sharpening methods in real and synthetic images

A. Medina, J. Marcello, F. Eugenio, D. Rodríguez, J. Martín

Proceedings Volume 8537, 853703 (2012) https://doi.org/10.1117/12.974566

KEYWORDS: Image fusion, Principal component analysis, Image quality, Wavelets, Image processing, Visualization, Multispectral imaging, Wavelet transforms, Spatial resolution, Lanthanum

Read Abstract +

Proceedings Article | 1 November 2012 Paper

Atmospheric correction models for high resolution WorldView-2 multispectral imagery: a case study in Canary Islands, Spain

J. Martin, F. Eugenio, J. Marcello, A. Medina, Juan A. Bermejo, M. Arbelo

Proceedings Volume 8534, 85340O (2012) https://doi.org/10.1117/12.974564

KEYWORDS: Atmospheric modeling, Atmospheric corrections, Reflectivity, Satellites, Sensors, Atmospheric monitoring, Image resolution, Remote sensing, Environmental monitoring, Atmospheric sensing

Read Abstract +

The emergence of high-resolution satellites with new spectral channels and the ability to change its viewing angle has highlighted the importance of modeling the atmospheric effects. So, atmospheric correction serves a critical role in the processing of remotely sensed image data, particularly with respect to identification of pixel content. Efficient and accurate realization of images in units of reflectance, rather than radiance, has proven to be a crucial point in the pre-processing of images in remote sensing applications, acquired under a variety of measurement conditions. However, reflectance of the objects recorded by satellite sensors is generally affected by atmospheric absorption and scattering, sensor-targetillumination geometry, and sensor calibration. These normally result in distortion of the actual reflectance of the objects that subsequently affects the extraction of information from images. The use of atmospheric models has significantly improved the results of the corrections. In this study we have proceeded to make the atmospheric correction of the eight multispectral bands of high resolution WorldView-2 satellite by three different atmospherics models (COST, DOS, 6S) defining the geometry of the satellite observation, viewing angle and setting the weather conditions more suited for the acquired images of the study area (Granadilla, Canary Islands). For this purpose, the reflectance obtained by COST, DOS and 6S atmospheric correction techniques are compared with the Top of Atmosphere (TOA) reflectance. Specifically, the 6S atmospheric correction model, based on radiative transfer theory, provides patterns which describe properly atmospheric conditions in this specific study area for monitoring turbid coastal environments. To check the proper functioning of the atmospheric correction comparison was performed between ground-based measurements and corresponding obtained by the eight multispectral satellite channels through the 6S atmospheric model, with similar date, weather and lighting conditions.

Proceedings Article | 25 October 2012 Paper

Monitoring El Hierro submarine volcano with low and high resolution satellite images

F. Eugenio, J. Marcello, J. Martin

Proceedings Volume 8538, 853816 (2012) https://doi.org/10.1117/12.974519

KEYWORDS: Satellites, Remote sensing, MODIS, Electroluminescence, Satellite imaging, Image processing, Data modeling, Earth observing sensors, Image resolution, Sensors

Read Abstract +

Proceedings Article | 23 October 2012 Paper

Analysis of regional vegetation changes with medium and high resolution imagery

J. Marcello, F. Eugenio, A. Medina

Proceedings Volume 8531, 85311R (2012) https://doi.org/10.1117/12.974385

KEYWORDS: Vegetation, Sensors, Image segmentation, Composites, Image resolution, Principal component analysis, Landsat, Image analysis, Satellites, Earth observing sensors

Read Abstract +

Proceedings Article | 16 November 2004 Paper

Validation of MODIS and AVHRR sea surface temperature using bulk measurements

Francisco Eugenio, Javier Marcello, Eduardo Rovaris

Proceedings Volume 5569, (2004) https://doi.org/10.1117/12.565277

KEYWORDS: Temperature metrology, Satellites, MODIS, Atmospheric corrections, In situ metrology, Radiometry, Algorithm development, Earth observing sensors, Lanthanum, Infrared radiation

Read Abstract +

Proceedings Article | 10 November 2004 Paper

Evaluation of thresholding techniques applied to oceanographic remote sensing imagery

Javier Marcello, Ferran Marques, Francisco Eugenio

Proceedings Volume 5573, (2004) https://doi.org/10.1117/12.565282

KEYWORDS: Image segmentation, Remote sensing, Expectation maximization algorithms, Synthetic aperture radar, Image sensors, Sensors, Satellites, Image processing, MODIS, Microwave radiation

Read Abstract +

Proceedings Article | 19 March 2003 Paper

Bayesian segmentation and clustering for determining cloud mask images

Dacil Barreto, Fionn Murtagh, Javier Marcello

Proceedings Volume 4877, (2003) https://doi.org/10.1117/12.463768

KEYWORDS: Expectation maximization algorithms, Clouds, Image segmentation, Data modeling, Quantization, Principal component analysis, Lanthanum, Visualization, Satellites, Computer science

Read Abstract +

Showing 5 of 12 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years