A method for rapid measurement of cloud base height from a pair of sky imagers

Cloud base height, a crucial spatial parameter of cloud clusters, plays a significant role in the field of photovoltaics and other domains. In order to obtain the cloud base height information of the whole sky, the cloud base height measurement technology based on binocular vision technology has been developed. However, the current global matching method yields a single value, while the computational efficiency of the local matching technique remains inadequate. This letter proposes a fast measurement method for determining cloud base height using a semi-local matching technique. First, the ground-based cloud image is segmented to reduce the calculation amount of cloud base height. Subsequently, the individual cloud blocks are divided into clusters through clustering. Finally, matching points are identified for each individual cloud section using feature detection and matching, allowing for the computation of the cloud base height at multiple feature points within each cloud section. The experimental results, based on ceilometer as a reference, show that the proposed method has better performance than the existing methods.