Automatic thresholding for digital hemispherical photography

Abstract

This paper proposes an automatic thresholding method for the discrimination of sky and canopy elements in color hemispherical photographs taken with a digital camera (Nikon Coolpix 950). The exposures for photography were principally determined on the basis of zenith luminance. DIF photo , which is diffuse transmittance calculated from the hemispherical photographs, was related to DIF sensor , which is diffuse transmittance measured directly with a photosynthetic photon flux density sensor. First, the thresholds for calculation of DIF photo were manually assessed in the photographs to obtain the best match with DIF sensor . At the lower pixel-value level in the pixel histograms from the photographs, L-shaped curves were always recognized, and the threshold occurred at the point with the maximum curvature. Second, an automatic thresholding algorithm, taking into account the position of the thresholds, was computerized. Third, the relationships between DIF photo and DIF sensor were field-tested across a wide range of light conditions. The method was effective in a planted coniferous forest and a natural broad-leaved forest and under overcast, twilit, and sunny sky conditions. The coefficients of determination between DIF sensor and DIF photo were greater than 0.99. However, DIF photo taken with Auto-Exposure was overestimated under dense canopy.Résumé : Cet article propose une méthode automatique de fixation du seuil pour distinguer le ciel et la canopée sur des photographies hémisphériques en couleurs prises avec une caméra digitale (Coolpix 950 de Nikon). L'exposition pour les photographies a été déterminée surtout sur la base de la luminance au zénith. DIF photo , qui est la transmittance diffuse calculée à partir des photographies hémisphériques, était relié à DIFcapteur, qui est la transmittance diffuse mesurée directement avec un capteur densité de flux photonique photosynthétique. Dans un premier temps, les seuils pour calculer DIF photo ont été évalués manuellement sur les photographies pour obtenir la meilleure relation avec DIFcapteur. Au niveau le plus bas de la valeur des pixels dans les histogrammes de pixels provenant des photographies, les courbes en forme de L étaient toujours détectées et le seuil était situé au point de courbure maximale. Dans un deuxième temps, un algorithme de détermination automatique du seuil qui tenait compte de la position des seuils a été calculé. Dans un troisième temps, les relations entre DIF photo et DIF capteur ont été testées sur le terrain pour une large gamme de conditions de lumière. La méthode était efficace dans une plantation de conifères et une forêt feuillue naturelle, sous des conditions de ciel nuageux, crépusculaire et ensoleillé. Les coefficients de détermination entre DIF capteur et DIF photo étaient supérieurs à 0,99. Cependant, avec une exposition automatique DIF photo était surestimé sous un couvert végétal dense.[Traduit par la Rédaction] Ishida 2216

Development of a Rapid and Precise Method of Digital Image Analysis to Quantify Canopy Density and Structural Complexity

“…In this way, the suitability of any given threshold could be examined in a "determination" stage and canopy then analysed using that threshold in a "quantification" stage. Theoretically, it should be possible to automate the determination stage, either fully or partially, using thresholdselection algorithms, and there have been several attempts to do this (e.g., [41,42]). However, these algorithms are not always successful in determining an appropriate threshold [43], especially when the relative contrast between vegetation and sky changes across the image (e.g., sun-illuminated vegetation against white cloud in one part of the image and shaded vegetation against bright blue sky in another part of the image) [44] and add substantially to processing time.…”

Light Intensity and Soil Compaction as Influenced by Ecotourism Activities in Pahang National Park, Malaysia

“…Lhotka and Loewenstein [13] suggested that the measurements were made under overcast conditions, usually in the late morning hours. The digital images were processed based on a procedure developed by Ishida [18]. All images were analyzed to calculate the percentage of diffuse light intensity under the canopy (SOC percentage) using RGBFisheye ver.2.01 (Gifu, Japan).…”

A 20-Year Overview of Quercus robur L. Mortality and Crown Conditions in Slovenia

“…The solar constant was defined as 1.370 W/m 2 , 0.6 was set for atmospheric transmissivity and 0.15 for the proportion of diffuse radiation compared to the calculated direct potential radiation. An automatic thresholding method based on the same color scheme was applied for the discrimination between sky and canopy elements in all digital photographs, as thresholding of the photographs is crucial and may significantly affect the calculated parameters [23]. The analysis was carried out for 120-degree angle of hemisphere, as it proved to be the best explaining angle [24].…”