WACODI: A generic algorithm to derive the intrinsic color of natural waters from digital images

Abstract

This document presents the WAter COlor from Digital Images (WACODI) algorithm, which extracts the color of natural waters from images collected by low-cost digital cameras, in the context of participatory science and water quality monitoring. SRGB images are converted to the CIE XYZ color space, undergoing a gamma expansion and illumination correction that includes the specular reflection at the air-water interface. The XYZ values obtained for each pixel of the image are converted to chromaticity coordinates and Hue color angle (αw), which is a measure of color. Based on the distributions of αw in sub-sections of the image, an approximation of the intrinsic color of the water is obtained. This algorithm was applied to images acquired in 2013 during two field campaigns in Northern Europe. The Hue color angles were derived from hyperspectral measurements above and below the surface, carried out simultaneously with image acquisition. When for each station a specific illumination correction was applied, based on the corresponding hyperspectral data, a good fit (r2 =0.93) was obtained between the image and the spectra Hue color angles (slope = 0.98, intercept =-0.03). When a more generic illumination correction was applied to the same images, based on the sky conditions at the time of the image acquisition (either overcast or sunny), a slightly inferior, but still satisfactory fit resulted. Results on the application of the WACODI algorithm to the first images collected by the public via the smartphone application or “APP,” developed within the European FP7 Citclops, are presented at the end of this study.