Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range Fernández Carvelo, Sol Martínez Domingo, Miguel Ángel Valero Benito, Eva María Romero Mora, Francisco Javier Nieves Gómez, Juan Luis Hernández Andrés, Javier Dehazing Hyperspectral Band selection Image quality metric The Spanish Ministry of Science Innovation and Universities (MICINN, grant number RTI2018-094738-B-100) and the Junta de Andalucia (grant number A-TIC-050-UGR18), both financed with FEDER Funds. 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. 2021-10-18T08:46:54Z 2021-10-18T08:46:54Z 2021-09-03 info:eu-repo/semantics/article Fernández-Carvelo, S... [et al.]. Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range. Sensors 2021, 21, 5935. [https://doi.org/10.3390/s21175935] http://hdl.handle.net/10481/70921 10.3390/s21175935 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI