CPD: A Lightweight Image Processing Framework for Cloud Presence Detection in UAV Imagery
Mark Phil B. Pacot, Nelson Marcos · 2025
Cloud presence in UAV imagery introduces radiometric distortions that degrade visual quality and interfere with downstream image analysis tasks. This paper presents CPD, a lightweight image processing framework for detecting cloud presence in UAV-acquired images. The proposed method leverages a combination of dark channel prior and local contrast measurement to generate a binary haze map for image-level classification. Unlike deep learning-based cloud detectors, CPD requires no training data and performs inference in a fast, scalable manner. To further improve runtime efficiency, we implement an optimized GPU-enhanced version using convolution-based approximations of morphological and statistical operators. Experimental results on three datasets, including public satellite and haze datasets as well as a UAV-based dataset, demonstrate the method’s accuracy and runtime advantage. CPD achieves over 99% detection accuracy with up to 5× runtime improvement on mid-range consumer hardware, validating its applicability in real-time UAV image processing pipelines.