Maria Soledad Fernandez Carvelo

I studied a bachelor's degree in physics as well as a master's degree in Geophisics and Meteorology at the University of Granada. I was working as Optical Engineer (signaling department) for a few years. Thereafter, I joined to the Color Imaging Lab group at the department of Optics of the University of Granada on the project “Automatic enhancement of images degraded by the atmosphere with multispectral techniques in the visible and infrared”. Nowadays, I am pursuing a PhD in the Atmospheric Physics group (GFAT) at the department of Applied Physic of University of Granada which focus on advanced remote sensing techniques for the study of atmospheric aerosol (LIDAR Technique) which is financed by a national grant for research initiation.

EDUCATION

- 2013: BSc. & MSc. Physics
- 2019: MSc. Meteorology (Physics of the Atmosphere)

RESEARCH INTERESTS

My research interests involve atmospheric optic, color, spectral imaging, dehazing, atmospheric aerosol and clouds interaction, remote sensing, fluorescence and LIDAR technique.

Scopus Publications

Band selection for dehazing algorithms applied to hyperspectral images in the visible range
Sol Fernández-Carvelo, Miguel Ángel Martínez-Domingo, Eva M. Valero, Javier Romero, Juan Luis Nieves, and Javier Hernández-Andrés
MDPI AG
Images captured under bad weather conditions (e.g., fog, haze, mist, dust, etc.), suffer from poor contrast and visibility, and color distortions. The severity of this degradation depends on the distance, the density of the atmospheric particles and the wavelength. We analyzed eight single image dehazing algorithms representative of different strategies and originally developed for RGB images, over a database of hazy spectral images in the visible range. We carried out a brute force search to find the optimum three wavelengths according to a new combined image quality metric. The optimal triplet of monochromatic bands depends on the dehazing algorithm used and, in most cases, the different bands are quite close to each other. According to our proposed combined metric, the best method is the artificial multiple exposure image fusion (AMEF). If all wavelengths within the range 450–720 nm are used to build a sRGB renderization of the imagaes, the two best-performing methods are AMEF and the contrast limited adaptive histogram equalization (CLAHE), with very similar quality of the dehazed images. Our results show that the performance of the algorithms critically depends on the signal balance and the information present in the three channels of the input image. The capture time can be considerably shortened, and the capture device simplified by using a triplet of bands instead of the full wavelength range for dehazing purposes, although the selection of the bands must be performed specifically for a given algorithm.